Anthropic
AI safety and research company behind Claude, focusing on constitutional AI.
5 Rounds
~20 Days
Very Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Backend Engineer
•
Behavioral
•
medium
Describe a time you had to debug a complex distributed systems failure in production. What was your methodology?
#Debugging
#Incident Response
#Distributed Systems
Backend Engineer
•
Behavioral
•
easy
Why Anthropic? With so many AI labs like OpenAI, DeepMind, and Meta, what specifically draws you to our mission and technical approach?
#Motivation
#Company Knowledge
#Alignment
Backend Engineer
•
Behavioral
•
medium
How do you handle situations where product requirements are highly ambiguous or rapidly changing, which is common in the fast-paced AI industry?
#Ambiguity
#Agile
#Communication
Backend Engineer
•
Behavioral
•
medium
Anthropic heavily values 'Helpful, Honest, and Harmless' (HHH). Tell me about a time you had to trade off between shipping a feature quickly and ensuring system safety or reliability.
#Safety
#Trade-offs
#Decision Making
Backend Engineer
•
Behavioral
•
medium
Describe a project where you had to significantly optimize the performance (latency, throughput, or cost) of a backend system. What metrics did you use?
#Performance Optimization
#Impact
#Metrics
Backend Engineer
•
Behavioral
•
medium
Tell me about a time you worked closely with researchers or data scientists to deploy a complex model or algorithm to production.
#Cross-functional
#Communication
#MLOps
Backend Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a technical decision made by your team or manager. How did you handle it, and what was the outcome?
#Conflict Resolution
#Leadership
#Communication
Backend Engineer
•
Coding
•
hard
Implement a streaming JSON parser that can take chunks of a JSON string (as they are generated by an LLM) and yield valid parsed objects as soon as they are complete.
#Parsing
#State Machines
#String Manipulation
Backend Engineer
•
Coding
•
medium
Implement a deep copy function for a complex graph data structure that may contain cycles. Ensure that nodes are duplicated correctly without infinite loops.
#Graph Theory
#Recursion
#Hash Map
Backend Engineer
•
Coding
•
medium
Implement an in-memory Event Bus (Pub/Sub system) where publishers can emit events and subscribers can listen to specific event types using regex patterns.
#Design Patterns
#Concurrency
#String Matching
Backend Engineer
•
Coding
•
hard
Write a function to merge K sorted asynchronous streams of data into a single sorted stream. You cannot load all data into memory at once.
#Heaps
#Asynchronous Programming
#Streaming
Backend Engineer
•
Coding
•
hard
Given a string representing a user prompt, find the longest repeating substring. This is useful for detecting repetitive loops in context windows.
#String Manipulation
#Dynamic Programming
#Suffix Trees
Backend Engineer
•
Coding
•
medium
Implement a Trie (Prefix Tree) that supports inserting strings, searching for exact matches, and finding all strings that share a given prefix. Optimize it for memory.
#Trees
#String Manipulation
#Memory Optimization
Backend Engineer
•
Coding
•
medium
Given a massive log file of API requests, write a script to find the 99th percentile latency. The file is too large to fit into memory.
#Data Processing
#Approximation Algorithms
#File I/O
Backend Engineer
•
Coding
•
medium
Implement a thread-safe LRU Cache with a Time-To-Live (TTL) for each item. Expired items should not be returned and should be cleaned up efficiently.
#Hash Map
#Linked List
#Concurrency
Backend Engineer
•
Coding
•
medium
Implement a thread-safe Rate Limiter using the Token Bucket algorithm. It should support multiple users and handle concurrent requests efficiently.
#Concurrency
#Data Structures
#API Design
Backend Engineer
•
Coding
•
medium
Implement a bounded blocking queue. It should support enqueue and dequeue operations, blocking when full or empty, respectively.
#Concurrency
#Synchronization
#Thread Safety
Backend Engineer
•
Coding
•
hard
Given a stream of tokens (strings), implement a data structure to efficiently find the top K most frequent tokens in a sliding window of the last N minutes.
#Streaming Data
#Heaps
#Sliding Window
Backend Engineer
•
Coding
•
hard
Write a program to justify text. Given an array of words and a max width, format the text such that each line has exactly max width characters and is fully (left and right) justified.
#String Manipulation
#Array
#Simulation
Backend Engineer
•
Coding
•
hard
Write an asynchronous task scheduler in Python (using asyncio) or Rust (using tokio) that executes a DAG (Directed Acyclic Graph) of tasks with maximum concurrency.
#Graph Theory
#Asynchronous Programming
#Concurrency
Backend Engineer
•
System Design
•
hard
Design a distributed prompt caching layer to optimize LLM inference costs. How do you handle cache invalidation and eviction for variable-length context windows?
#Caching
#Distributed Systems
#Optimization
Backend Engineer
•
System Design
•
medium
Design a distributed ID generator that generates unique, k-sortable (time-ordered) 64-bit integers at a scale of millions per second.
#Distributed Systems
#Algorithms
#Scalability
Backend Engineer
•
System Design
•
hard
Design a Vector Database architecture for Retrieval-Augmented Generation (RAG). How do you scale the index for billions of embeddings while maintaining low-latency ANN (Approximate Nearest Neighbor) search?
#Vector Databases
#Machine Learning Infrastructure
#Search
Backend Engineer
•
System Design
•
hard
Design an abuse detection system that monitors API usage patterns to detect and block malicious actors (e.g., prompt injection attacks, DDOS, account sharing) in near real-time.
#Security
#Stream Processing
#Machine Learning Infrastructure
Backend Engineer
•
System Design
•
medium
Design an asynchronous web scraper for training data collection. It must respect robots.txt, handle rate limits, and scale to scrape millions of domains daily.
#Web Scraping
#Distributed Systems
#Concurrency
Backend Engineer
•
System Design
•
hard
Design a telemetry and observability system for LLM safety guardrails. It needs to ingest billions of events per day and allow for real-time alerting on policy violations.
#Data Ingestion
#Stream Processing
#Observability
Backend Engineer
•
System Design
•
hard
Design a system to schedule and batch LLM inference requests across a cluster of GPUs to maximize throughput while respecting latency SLAs.
#Batching
#Resource Scheduling
#Queueing Theory
Backend Engineer
•
System Design
•
medium
Design a system to handle long-running asynchronous model fine-tuning jobs. How do you manage state, handle node failures, and provide progress updates to users?
#Job Scheduling
#State Machines
#Fault Tolerance
Backend Engineer
•
System Design
•
hard
Design a scalable rate-limiting service for the Claude API that can handle millions of requests per minute across globally distributed data centers.
#Distributed Systems
#Redis
#High Availability
Backend Engineer
•
System Design
•
hard
Design a real-time streaming inference API for an LLM. How do you handle connection drops, partial token generation, and backpressure?
#Server-Sent Events (SSE)
#WebSockets
#Streaming
#Network Protocols
Backend Engineer
•
System Design
•
medium
Design a highly available key-value store to maintain user session history (chat logs) for Claude. It must support high write throughput and fast sequential reads.
#Databases
#Replication
#Data Modeling
Backend Engineer
•
Technical
•
medium
How do you handle backpressure in a distributed messaging queue when the consumers (e.g., GPU inference nodes) are overwhelmed?
#Message Queues
#System Reliability
#Backpressure
Backend Engineer
•
Technical
•
hard
How would you optimize a Rust backend for high-throughput, low-latency network I/O? Discuss memory allocation, async runtimes, and socket tuning.
#Rust
#Networking
#Performance Optimization
Backend Engineer
•
Technical
•
medium
Explain how Python's Global Interpreter Lock (GIL) impacts concurrent API requests. How would you architect a high-throughput Python backend to bypass these limitations?
#Python
#Concurrency
#Multiprocessing
Backend Engineer
•
Technical
•
hard
Describe how you would implement zero-downtime deployments for a backend service that maintains long-lived stateful streaming connections (like SSE for LLM responses).
#Deployments
#Networking
#High Availability
Cloud Engineer
•
Behavioral
•
medium
You receive an alert that API latency has spiked by 400% in the last 5 minutes. Walk me through your incident response and debugging process.
#Troubleshooting
#On-call
#Communication
#Root Cause Analysis
Cloud Engineer
•
Behavioral
•
medium
Walk me through your troubleshooting process for a Sev-1 incident where latency for the Claude API spikes by 500% across all regions. What metrics do you look at first?
#Troubleshooting
#SRE
#On-call
#Root Cause Analysis
Cloud Engineer
•
Behavioral
•
medium
Anthropic prioritizes safety and reliability. Tell me about a time you had to push back on a deployment or architectural decision because it compromised system security or reliability, even when facing tight deadlines.
#Communication
#Safety
#Stakeholder Management
#Ethics
Cloud Engineer
•
Behavioral
•
easy
Tell me about a time you automated a tedious operational task. What was the impact, and how did you measure success?
#Toil Reduction
#Automation
#Impact Measurement
Cloud Engineer
•
Behavioral
•
hard
How do you balance the need for rapid iteration by AI researchers with the need for stable, secure, and cost-effective infrastructure?
#Developer Experience
#Governance
#Cost Optimization
#Agility
Cloud Engineer
•
Behavioral
•
medium
Describe a situation where you had to learn a completely new technology under a tight deadline to solve a critical infrastructure problem.
#Adaptability
#Continuous Learning
#Problem Solving
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you had to push back on a feature request or architectural decision because it compromised security or reliability.
#Communication
#Conflict Resolution
#Security First
Cloud Engineer
•
Behavioral
•
medium
Anthropic places a high value on AI safety. How do you see the role of a Cloud Engineer contributing to the safety and security of our models?
#AI Safety
#Security
#Infrastructure Integrity
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you caused a production outage. How did you handle it, and what did you learn?
#Ownership
#Blameless Postmortems
#Learning from Failure
Cloud Engineer
•
Coding
•
easy
Write a bash script to parse a large Nginx access log file, extract the top 10 IP addresses making requests to a specific API endpoint, and dynamically block them using iptables.
#Bash
#Linux
#Networking
#Security
Cloud Engineer
•
Coding
•
medium
Write a script to automatically scale an Auto Scaling Group based on a custom metric (e.g., GPU memory utilization) retrieved from Prometheus.
#Python
#Prometheus API
#AWS Auto Scaling
#Automation
Cloud Engineer
•
Coding
•
hard
Given a JSON response from a cloud API containing nested resource dependencies, write an algorithm to determine the correct deletion order.
#Graphs
#Topological Sort
#DFS
#JSON Parsing
Cloud Engineer
•
Coding
•
easy
Write a function to parse a large Nginx access log file and return the top 10 IP addresses with the highest HTTP 5xx error rates.
#Python
#Log Parsing
#Data Structures
#Regex
Cloud Engineer
•
Coding
•
medium
Implement a concurrent worker pool in Go to process a large queue of infrastructure provisioning tasks efficiently.
#Go
#Concurrency
#Goroutines
#Channels
Cloud Engineer
•
Coding
•
medium
Write a Python script using `boto3` to find and delete all unattached EBS volumes in an AWS account that are older than 30 days.
#Python
#Boto3
#AWS EC2
#Automation
Cloud Engineer
•
Coding
•
medium
Write a Terraform snippet to create an AWS IAM role that can only be assumed by a specific Kubernetes service account (IRSA).
#Terraform
#AWS IAM
#EKS
#Security
Cloud Engineer
•
Coding
•
medium
Write a Go program that concurrently health-checks a list of internal model endpoints. It should implement a worker pool, timeout after 2 seconds per request, and aggregate the results into a summary report.
#Go
#Concurrency
#Networking
#Error Handling
Cloud Engineer
•
Coding
•
medium
Write a Python script using boto3 to identify and terminate orphaned EC2 GPU instances that have been idle for more than 4 hours, ensuring they aren't part of an active Ray cluster.
#Python
#AWS API
#Cloud Cost Optimization
#Scripting
Cloud Engineer
•
System Design
•
hard
Design a multi-region Kubernetes cluster architecture to support distributed LLM training workloads. How do you handle GPU node provisioning, network topology, and fault tolerance?
#Kubernetes
#GPU Compute
#Distributed Systems
#AWS/GCP
Cloud Engineer
•
System Design
•
medium
Design an observability pipeline capable of handling millions of metrics and logs per second from our Kubernetes clusters.
#Prometheus
#Grafana
#OpenTelemetry
#Log Aggregation
Cloud Engineer
•
System Design
•
hard
Design the observability stack for a fleet of thousands of GPU instances. How do you collect, aggregate, and alert on GPU memory utilization and temperature without overwhelming the metrics backend?
#Observability
#Prometheus
#Grafana
#Scaling
Cloud Engineer
•
System Design
•
hard
Design a global rate-limiting service for the Claude API that needs to handle millions of requests per minute, ensuring strict token-based quota enforcement per customer tier.
#Redis
#Distributed Systems
#API Gateway
#Scalability
Cloud Engineer
•
System Design
•
hard
Design a multi-region active-active inference API for Claude. How do you handle routing, state, and failover?
#Global Routing
#High Availability
#Load Balancing
#Multi-Region
Cloud Engineer
•
System Design
•
hard
How would you design a scalable infrastructure to manage and provision thousands of GPUs for distributed training jobs?
#GPU Provisioning
#AWS EC2
#Kubernetes
#HPC Networking
Cloud Engineer
•
System Design
•
medium
Design a rate-limiting service for our public API that handles sudden spikes in token generation requests across millions of users.
#Rate Limiting
#Redis
#Distributed Systems
#API Gateway
Cloud Engineer
•
System Design
•
hard
Design a high-throughput storage solution for feeding petabytes of text data into a distributed training cluster. Compare using S3 directly vs. FSx for Lustre.
#Storage
#High Performance Computing
#AWS
#Data Pipelines
Cloud Engineer
•
System Design
•
medium
How would you design a deployment pipeline to safely roll out a new version of the Claude model to production with zero downtime?
#Blue/Green Deployment
#Canary Releases
#Traffic Shadowing
#Rollbacks
Cloud Engineer
•
System Design
•
hard
Architect a secure storage and retrieval system for massive datasets used in model training, ensuring high throughput and strict access controls.
#AWS S3
#IAM
#Data Security
#Throughput Optimization
Cloud Engineer
•
Technical
•
medium
Explain how you would troubleshoot a CrashLoopBackOff error in a pod that is supposed to be loading a 100GB model weight file from S3 into memory.
#Kubernetes
#OOMKilled
#Liveness Probes
#Init Containers
Cloud Engineer
•
Technical
•
easy
Explain the RED metrics. How would you apply them to a microservice architecture?
#Metrics
#Monitoring
#SRE
Cloud Engineer
•
Technical
•
hard
How do you define and measure Service Level Objectives (SLOs) for an LLM inference service where latency can vary heavily based on prompt length?
#SLIs/SLOs
#Metrics
#LLM Infrastructure
#Performance
Cloud Engineer
•
Technical
•
medium
How do you manage sensitive secrets (like API keys or database passwords) in Terraform without exposing them in the state file or version control?
#Terraform
#Secret Management
#AWS Secrets Manager
#HashiCorp Vault
Cloud Engineer
•
Technical
•
medium
You need to manage infrastructure for a new AI research environment. How would you structure the Terraform state and modules to ensure strict isolation between research teams while sharing core networking components?
#Terraform
#State Management
#Security
#VPC
Cloud Engineer
•
Technical
•
hard
Explain how you would design a secure VPC architecture on AWS to allow Claude inference containers to access external customer APIs (e.g., for tool use) without exposing the inference nodes to the public internet.
#VPC
#NAT Gateway
#Egress Filtering
#Security
Cloud Engineer
•
Technical
•
medium
How would you configure Kubernetes pod anti-affinity, taints, and tolerations to ensure that critical inference API pods are not evicted by heavy batch research workloads on a shared cluster?
#Kubernetes
#Scheduling
#Resource Management
Cloud Engineer
•
Technical
•
medium
Describe how you would implement least-privilege IAM roles for a CI/CD pipeline (e.g., GitHub Actions) that needs to deploy infrastructure to AWS using OIDC.
#IAM
#OIDC
#CI/CD
#AWS Security
Cloud Engineer
•
Technical
•
hard
How would you design a deployment pipeline for updating the base Docker image of our inference service with zero downtime, ensuring that active WebSocket connections to Claude are gracefully drained?
#Docker
#Zero-downtime Deployment
#Load Balancing
#WebSockets
Cloud Engineer
•
Technical
•
medium
GPU compute is our biggest expense. What strategies would you implement at the cloud infrastructure level to optimize costs for ephemeral ML training jobs without slowing down research?
#FinOps
#Spot Instances
#Auto-scaling
#AWS EC2
Cloud Engineer
•
Technical
•
medium
How would you structure Terraform modules for a multi-environment (dev, staging, prod) setup to maximize reuse and minimize blast radius?
#Terraform
#Module Design
#CI/CD
#Environment Isolation
Cloud Engineer
•
Technical
•
medium
You have a Terraform state file that has become out of sync with the actual AWS infrastructure due to manual console changes. How do you resolve this safely?
#Terraform
#State Management
#Drift Resolution
Cloud Engineer
•
Technical
•
medium
How do you handle graceful shutdown of a pod serving long-running LLM inference requests that might take up to 60 seconds to complete?
#Pod Lifecycle
#PreStop Hooks
#Termination Grace Period
#Load Balancing
Cloud Engineer
•
Technical
•
hard
Describe how you would implement network policies in a multi-tenant Kubernetes cluster to strictly isolate research workloads from production inference.
#Network Policies
#Cilium
#Calico
#Zero Trust
Cloud Engineer
•
Technical
•
medium
What are the challenges of running stateful workloads in Kubernetes, and how would you handle persistent storage for a distributed vector database?
#StatefulSets
#Persistent Volumes
#CSI
#Distributed Databases
Cloud Engineer
•
Technical
•
medium
How do you configure Kubernetes to efficiently schedule pods that require specific GPU types (e.g., A100 vs H100) while maximizing utilization?
#Node Selectors
#Taints and Tolerations
#GPU Scheduling
#Resource Quotas
Cloud Engineer
•
Technical
•
medium
Describe how you would mitigate a Layer 7 DDoS attack targeting our inference API endpoints.
#DDoS Mitigation
#WAF
#CloudFront
#Rate Limiting
Cloud Engineer
•
Technical
•
hard
What mechanisms would you put in place to prevent data exfiltration from a cloud environment hosting proprietary model weights?
#Data Exfiltration
#VPC Flow Logs
#Egress Filtering
#DLP
Cloud Engineer
•
Technical
•
medium
Explain how AWS Transit Gateway works and how you would use it to connect dozens of VPCs across different AWS accounts.
#AWS Transit Gateway
#VPC Peering
#Hub and Spoke
#Routing
Cloud Engineer
•
Technical
•
medium
How would you design an IAM strategy to enforce least privilege for researchers needing temporary access to specific S3 buckets containing training data?
#AWS IAM
#ABAC
#RBAC
#Temporary Credentials
Cloud Engineer
•
Technical
•
medium
Walk me through the process of establishing a secure, private connection between an AWS VPC and a third-party SaaS provider without routing traffic over the public internet.
#AWS PrivateLink
#VPC Endpoints
#Networking
#Security
Cloud Engineer
•
Technical
•
easy
Explain the difference between `count` and `for_each` in Terraform. When would you use one over the other?
#Terraform
#Syntax
#Resource Iteration
Data Engineer
•
Behavioral
•
medium
Anthropic places a heavy emphasis on 'Constitutional AI' and safety. How do you ensure your day-to-day engineering work aligns with broad ethical guidelines and safety standards?
#Alignment
#Ethics
#Company Values
Data Engineer
•
Behavioral
•
hard
Walk me through the most complex data pipeline you've ever built from scratch. What were the bottleneck constraints (CPU, memory, network, or I/O), and how did you measure and overcome them?
#Architecture
#Performance Profiling
#Problem Solving
Data Engineer
•
Behavioral
•
medium
Tell me about a time you had to push back on a product or research request because you had concerns about data safety, privacy, or quality.
#Communication
#Safety
#Integrity
Data Engineer
•
Behavioral
•
medium
Tell me about a time you had to debug a complex, distributed data pipeline failure under severe time pressure. What was your methodology?
#Debugging
#Incident Response
#Pressure
Data Engineer
•
Behavioral
•
easy
Tell me about a time you had to learn a completely new technology stack or domain (like transitioning from traditional ETL to ML data engineering) under a tight deadline.
#Adaptability
#Learning
#Agility
Data Engineer
•
Behavioral
•
medium
Anthropic highly values intellectual honesty. Tell me about a time you made a significant technical mistake that impacted a project. How did you handle it and what did you learn?
#Intellectual Honesty
#Growth Mindset
#Accountability
Data Engineer
•
Behavioral
•
medium
How do you prioritize tasks when supporting multiple fast-moving AI research teams with competing data needs and tight deadlines?
#Prioritization
#Stakeholder Management
#Agile
Data Engineer
•
Behavioral
•
medium
Describe a situation where you had to debug a complex, distributed data issue in production where there were no clear error logs or obvious failures.
#Debugging
#Problem Solving
#Resilience
Data Engineer
•
Behavioral
•
medium
Anthropic places a heavy emphasis on AI safety and Constitutional AI. Tell me about a time you had to push back on a project or feature because of data privacy, security, or ethical concerns. How did you handle the stakeholder conversation?
#AI Safety
#Stakeholder Management
#Ethics
Data Engineer
•
Behavioral
•
medium
How do you balance the need for rapid iteration and experimentation in AI research with the need for robust, reliable, and scalable data engineering practices?
#Trade-offs
#Research vs Engineering
#Prioritization
Data Engineer
•
Behavioral
•
medium
Anthropic focuses heavily on AI safety. Tell me about a time you identified a potential privacy, security, or safety risk in a dataset or pipeline. How did you raise the issue and what was the outcome?
#Safety
#Communication
#Ethics
Data Engineer
•
Behavioral
•
medium
Data Engineers at Anthropic work closely with ML Researchers whose requirements change rapidly based on experimental results. Tell me about a time you built a data pipeline or tool where the requirements were highly ambiguous or changed midway through development.
#Ambiguity
#Agile
#Cross-functional Teamwork
Data Engineer
•
Behavioral
•
easy
Tell me about a time you optimized a system or pipeline that resulted in significant cost or time savings. Walk me through the technical details of the bottleneck and your solution.
#Optimization
#Impact
#Problem Solving
Data Engineer
•
Coding
•
medium
Write a function that takes a stream of text and a target keyword, and returns a sliding window of N tokens before and after every occurrence of the keyword. Handle edge cases like overlapping windows.
#Sliding Window
#Text Processing
#Queues
Data Engineer
•
Coding
•
medium
Write a Python generator function to efficiently parse a 500GB JSONL file containing web crawl data, filtering out documents that do not contain a specific set of keywords, without loading the entire file into memory.
#Python
#Generators
#Memory Management
#File I/O
Data Engineer
•
Coding
•
medium
Write a SQL query to calculate the 30-day rolling average of tokens processed per model version, given a table of daily token usage logs.
#Window Functions
#Aggregations
#Time Series
Data Engineer
•
Coding
•
medium
Given a table of API requests containing `user_id`, `timestamp`, `prompt_tokens`, and `completion_tokens`, write a SQL query to find the top 3 users by total token usage for each day over the last 30 days, including a rolling 7-day average of their token usage.
#Window Functions
#Aggregations
#Time-series Data
Data Engineer
•
Coding
•
hard
Write a Python function to efficiently find near-duplicate text documents in a large corpus. You do not need to implement the full distributed system, but implement the core hashing logic (e.g., MinHash) and explain how you would scale it across a cluster.
#Hashing
#Text Processing
#Optimization
Data Engineer
•
Coding
•
medium
Write a Python program that takes a massive JSONL file of Wikipedia articles and chunks the text into overlapping segments of exactly 512 tokens (assume a simple whitespace tokenizer for this exercise), while preserving the document metadata in each chunk. The file is larger than available RAM.
#Generators
#Memory Management
#Text Processing
Data Engineer
•
Coding
•
medium
Given a table of raw chat interactions (`interaction_id`, `user_id`, `timestamp`, `message`), write a SQL query to group these interactions into 'sessions'. A new session starts if there is a gap of more than 30 minutes between messages from the same user.
#Gaps and Islands
#Window Functions
#Data Modeling
Data Engineer
•
Coding
•
medium
Given a table of user prompts, write a SQL query to find the top 3 most frequent prompt categories for each user. Include ties if they exist.
#Window Functions
#Ranking
#CTEs
Data Engineer
•
Coding
•
medium
Implement a rate limiter in Python for our API. The rate limiter should allow a user to make up to N requests per minute, but also enforce a maximum of M tokens generated per day. How would you make this distributed across multiple API servers?
#Data Structures
#Concurrency
#API Design
Data Engineer
•
Coding
•
medium
You have a table of model evaluation scores in a long format: (model_id, eval_metric, score). Write a SQL query to pivot this table so that 'Helpfulness', 'Honesty', and 'Harmlessness' are columns.
#Pivot
#Data Transformation
#Aggregations
Data Engineer
•
Coding
•
medium
Write a SQL query to calculate the Day-1, Day-7, and Day-30 retention rate of users interacting with the Claude API, grouped by the month they signed up.
#Cohorts
#Retention
#Date Math
Data Engineer
•
Coding
•
medium
In our distributed logging system, log IDs are supposed to be sequential. Write a SQL query to find all gaps (missing sequential IDs) in the log table.
#Gaps and Islands
#Sequences
#Self Joins
Data Engineer
•
Coding
•
hard
Write a SQL query to find the median model response latency per day from a massive logs table, assuming your SQL dialect does not have a built-in MEDIAN() function.
#Percentiles
#Math
#Advanced SQL
Data Engineer
•
Coding
•
hard
We have a log table of safety filter triggers. Write a SQL query to identify all user sessions where a user triggered a safety filter more than 3 times within any 5-minute window.
#Self Joins
#Time Series
#Complex Window Functions
Data Engineer
•
Coding
•
medium
Given a massive table of web crawl documents with `doc_id`, `url`, `content_hash`, and `crawled_at`, write a highly optimized SQL query to keep only the most recent version of each document per URL, but flag URLs that have multiple distinct content hashes over time.
#Window Functions
#Deduplication
#Data Cleaning
Data Engineer
•
Coding
•
medium
Write a Python function to process a 500GB JSONL file of raw text data. You need to filter out documents containing specific blocklisted keywords, compute a basic word count across the valid documents, and output the clean data to a new file. You have 8GB of RAM.
#Python
#Generators
#Memory Management
#I/O
Data Engineer
•
Coding
•
hard
Implement a distributed rate limiter in Python. Assume this will be used to throttle API requests for our Claude models based on a user's tier (e.g., tokens per minute).
#Concurrency
#Redis
#Token Bucket
#Distributed Systems
Data Engineer
•
Coding
•
medium
Given a list of overlapping time intervals representing periods when a GPU cluster was fully utilized, write a function to merge all overlapping intervals and return the total duration of full utilization.
#Sorting
#Intervals
#Python
Data Engineer
•
Coding
•
hard
Write a SQL query to calculate the 7-day rolling average of token usage per user, but only for users who have exceeded 10,000 tokens in at least three distinct days within the last month.
#Advanced SQL
#Rolling Averages
#Subqueries
Data Engineer
•
Coding
•
medium
Implement a Trie (Prefix Tree) data structure in Python. Then, write a method to find all words in the Trie that share a given prefix. Explain how this relates to LLM tokenization.
#Data Structures
#Trees
#String Manipulation
Data Engineer
•
Coding
•
hard
You have a stream of incoming chat logs. Write a Python algorithm to maintain the top K most frequent words over a sliding window of 1 hour.
#Streaming Algorithms
#Heaps
#Sliding Window
Data Engineer
•
Coding
•
hard
Write a SQL query to find the 'sessionization' of user interactions. Group consecutive user prompts into a single session if they occur within 30 minutes of each other. Output the user_id, session_start, session_end, and prompt_count.
#Sessionization
#Window Functions
#Time Series
Data Engineer
•
Coding
•
medium
Write a Python script that implements a custom MapReduce framework using the `multiprocessing` library to count the frequency of n-grams in a large corpus of text files.
#Concurrency
#MapReduce
#Python
Data Engineer
•
Coding
•
hard
Given a directed acyclic graph (DAG) representing data pipeline dependencies, write a Python function to execute the tasks in parallel where possible, respecting the dependency order. Assume each task is a sleep function.
#Graphs
#Topological Sort
#Concurrency
Data Engineer
•
Coding
•
medium
Write a SQL query to find the top 3 most frequently used prompt templates per user, but exclude templates that consist entirely of stop words (assume a `stop_words` table exists).
#Joins
#Filtering
#Window Functions
Data Engineer
•
Coding
•
hard
Given a massive string of text, write an algorithm to find the longest repeating substring. This is a simplified version of finding duplicated boilerplate text in web scrapes.
#String Algorithms
#Suffix Arrays
#Dynamic Programming
Data Engineer
•
Coding
•
hard
Given two large documents, write an algorithm to find the longest common contiguous substring. This is used in our pipeline to detect data contamination between training and evaluation sets.
#Dynamic Programming
#Suffix Trees
#Strings
Data Engineer
•
Coding
•
medium
Write a program to compute the top K most frequent tokens in a continuous, infinite stream of text. Optimize for both time and space complexity.
#Heaps
#Hash Maps
#Streaming
Data Engineer
•
Coding
•
hard
Implement a thread-safe Token Bucket rate limiter in Python. This will be used to throttle incoming requests to our data ingestion API to prevent overwhelming the downstream Kafka cluster.
#Concurrency
#Rate Limiting
#System Design
Data Engineer
•
Coding
•
easy
Given a list of text spans representing PII (Personally Identifiable Information) redactions in a document, where each span is a tuple of (start_index, end_index), write a function to merge all overlapping spans.
#Intervals
#Arrays
#Sorting
Data Engineer
•
Coding
•
medium
We need to create a pre-training dataset with a specific language distribution (e.g., 60% English, 20% Spanish, 20% French). Write a script to sample proportionally from a massive, unsorted stream of multilingual documents.
#Sampling
#Probability
#Streaming Algorithms
Data Engineer
•
Coding
•
hard
Given a massive dataset of text documents, implement a MinHash and Locality-Sensitive Hashing (LSH) algorithm in Python to identify near-duplicate documents. How would you scale this across a distributed cluster?
#Hashing
#Deduplication
#Big Data
#Distributed Systems
Data Engineer
•
System Design
•
medium
Design an experiment management system to track hyperparameter tuning, dataset versions, and evaluation metrics for thousands of concurrent LLM training runs.
#MLOps
#Database Design
#API Design
Data Engineer
•
System Design
•
hard
Design a data ingestion and processing pipeline to handle 10PB of raw web scrape data. The pipeline must perform exact and fuzzy deduplication, remove PII, and format the output into tokenized chunks for LLM pre-training.
#Distributed Systems
#Data Pipelines
#MinHash/LSH
#MapReduce
Data Engineer
•
System Design
•
hard
Design a system to securely handle, detect, and anonymize PII (Personally Identifiable Information) in petabytes of training datasets before they reach the ML models.
#Security
#PII
#Compliance
#NLP
Data Engineer
•
System Design
•
medium
How do you handle schema evolution in a massive data pipeline where upstream data formats (like web crawl schemas or partner data) change frequently without notice?
#Schema Evolution
#Data Quality
#Data Contracts
Data Engineer
•
System Design
•
medium
Design a highly scalable web scraper to build a high-quality dataset of academic papers. How do you handle rate limiting, IP bans, and parsing diverse PDF layouts?
#Web Scraping
#Distributed Systems
#Queues
#Unstructured Data
Data Engineer
•
System Design
•
hard
Design a system to track data lineage for datasets used in training Claude. If a researcher finds a toxic output, how do we trace it back to the specific training document?
#Data Lineage
#Governance
#Metadata Management
Data Engineer
•
System Design
•
medium
How would you architect a data lake at Anthropic to support both ML researchers needing raw text blobs and business analysts needing structured API usage metrics?
#Data Lake
#Architecture
#Storage Formats
#Governance
Data Engineer
•
System Design
•
hard
Design a distributed data processing framework to tokenize petabytes of text data efficiently. How do you handle vocabulary updates and ensure reproducibility?
#Distributed Systems
#MapReduce
#Tokenization
#Reproducibility
Data Engineer
•
System Design
•
medium
Design an automated evaluation pipeline that runs nightly benchmarks on the latest model checkpoints. The pipeline needs to run thousands of prompts, score them using another LLM, and aggregate the results.
#Orchestration
#CI/CD for ML
#Airflow
#Batch Inference
Data Engineer
•
System Design
•
hard
How would you design a system to handle continuous, high-throughput updates to a vector database used for Retrieval-Augmented Generation (RAG) without impacting read performance?
#Vector Databases
#RAG
#Data Sync
#Concurrency
Data Engineer
•
System Design
•
hard
Design a real-time monitoring system to track model inference latency and safety filter trigger rates across millions of requests per minute. How do you ensure low latency for the dashboard?
#Streaming
#Monitoring
#Metrics
#Kafka
#Druid/Pinot
Data Engineer
•
System Design
•
hard
Design a data pipeline to ingest, clean, and deduplicate 100TB of raw web crawl data for LLM pre-training. Walk me through the architecture, tools, and how you handle failures.
#Batch Processing
#Data Pipelines
#LLM Training
#Spark
Data Engineer
•
System Design
•
hard
Design a data architecture to support automated model evaluations. Every time a new model checkpoint is saved, it needs to be run against 10,000 benchmark datasets. How do you manage the orchestration, store the results, and provide a dashboard for researchers to compare model versions?
#Orchestration
#Airflow/Dagster
#Data Modeling
#CI/CD for ML
Data Engineer
•
System Design
•
hard
Design a real-time monitoring and alerting system for Claude's inference endpoints. The system needs to track latency, error rates, and token generation speed (Time to First Token, Tokens per Second), processing millions of events per minute with sub-second alerting latency.
#Stream Processing
#Kafka
#Observability
#Real-time Analytics
Data Engineer
•
System Design
•
hard
Design a scalable data pipeline to ingest, deduplicate, and filter 50TB of raw web scrape data per day to be used for pre-training a large language model. How do you handle PII scrubbing and ensure high data quality at this scale?
#Distributed Systems
#Data Pipelines
#Data Quality
#MapReduce/Spark
Data Engineer
•
System Design
•
hard
Design a distributed vector embedding storage and retrieval system. Researchers need to perform KNN searches on billions of embeddings generated from our models.
#Vector Databases
#KNN/ANN
#Distributed Systems
Data Engineer
•
System Design
•
medium
Design a scalable backend system for collecting RLHF (Reinforcement Learning from Human Feedback) data. Human annotators will be comparing two model outputs. The system must ensure no data loss, handle annotator concurrency, and output training-ready datasets.
#Transactional Databases
#Concurrency
#API Design
Data Engineer
•
System Design
•
hard
Design a system to track data provenance and lineage for Constitutional AI training sets. If a specific document is found to be corrupted, we need to know exactly which model checkpoints were trained on it.
#Data Lineage
#Metadata Management
#Graph Databases
Data Engineer
•
System Design
•
hard
Design a distributed task queue specifically optimized for scheduling offline batch inference jobs on GPUs. Some jobs take seconds, others take days. GPUs are heterogeneous (e.g., A100s vs H100s).
#Task Queues
#Resource Scheduling
#Distributed Systems
Data Engineer
•
System Design
•
hard
Design a real-time monitoring and alerting system for LLM inference. It needs to track latency, token generation speed, and run a lightweight toxicity classifier on the output stream. How do you handle spikes of 100,000 requests per second?
#Stream Processing
#Kafka
#Real-time Analytics
#Monitoring
Data Engineer
•
System Design
•
hard
Design a multi-region active-active data replication system for model checkpoints. Each checkpoint is 100GB, and they are generated every hour. Researchers globally need fast access to the latest checkpoints.
#Data Replication
#Cloud Storage
#Network Optimization
Data Engineer
•
System Design
•
hard
Design an evaluation pipeline that runs 50,000 complex prompts against multiple versions of an LLM daily. The pipeline must aggregate scores, compute regressions, and block model deployment if safety thresholds are breached.
#Batch Processing
#CI/CD for ML
#Airflow/Dagster
Data Engineer
•
Technical
•
medium
How do you ensure reproducibility in data pipelines used for machine learning? If a researcher asks for the exact dataset used to train a model 6 months ago, how do you provide it?
#Reproducibility
#Data Versioning
#MLOps
Data Engineer
•
Technical
•
hard
In Apache Spark, how would you handle a situation where a `join` operation causes severe data skew, specifically when processing text data where certain domains (e.g., Wikipedia) are vastly overrepresented?
#Apache Spark
#Data Skew
#Performance Optimization
Data Engineer
•
Technical
•
medium
Explain the trade-offs between Parquet, Avro, and JSONL formats. Which would you choose for storing intermediate RLHF (Reinforcement Learning from Human Feedback) data, and why?
#File Formats
#Storage Optimization
#Schema Evolution
Data Engineer
•
Technical
•
medium
Describe your approach to implementing strict data quality checks for safety-critical datasets. How do you prevent 'bad' data from silently corrupting a model training run?
#Data Quality
#Testing
#Anomaly Detection
Data Engineer
•
Technical
•
medium
How do you manage schema evolution in a rapidly changing data environment where AI researchers are constantly adding new metadata fields to evaluation logs?
#Schema Evolution
#Data Governance
#Protobuf/Thrift
Data Engineer
•
Technical
•
hard
During a distributed Spark job to compute vocabulary frequencies across our training corpus, you encounter severe data skew because some words (like 'the') appear orders of magnitude more often than others, causing out-of-memory errors on specific worker nodes. How do you resolve this?
#Apache Spark
#Data Skew
#Distributed Computing
#Performance Tuning
Data Engineer
•
Technical
•
hard
What strategies do you use to minimize cloud storage and compute costs for petabyte-scale datasets while maintaining high read throughput for ML training clusters?
#Cloud Architecture
#Cost Optimization
#Caching
Data Engineer
•
Technical
•
hard
What are the challenges of managing state in streaming applications (e.g., Apache Flink) compared to batch processing, particularly when dealing with late-arriving data?
#Stream Processing
#State Management
#Watermarks
Data Engineer
•
Technical
•
medium
For Constitutional AI, we rely on high-quality human preference data (RLHF). If you have a pipeline receiving human-annotated rankings of model outputs, what automated data quality checks would you implement to detect spammy, biased, or low-effort annotators?
#Anomaly Detection
#Data Validation
#Heuristics
Data Engineer
•
Technical
•
hard
Explain how you would build a pipeline to keep a vector database updated in near real-time as underlying source documents change (inserts, updates, deletes). How do you handle embedding versioning when the embedding model itself is updated?
#Vector Databases
#RAG
#Change Data Capture (CDC)
#Embeddings
Data Engineer
•
Technical
•
hard
Explain how you would implement backpressure in a streaming data pipeline. What happens if the downstream consumer (e.g., an ML inference endpoint) goes down?
#Streaming
#Architecture
#Resilience
Data Engineer
•
Technical
•
medium
How do you ensure data quality and detect statistical drift in a continuous ingestion pipeline feeding an active learning system?
#Data Quality
#Anomaly Detection
#Observability
Data Engineer
•
Technical
•
medium
Describe the trade-offs between columnar storage formats like Parquet and row-based storage formats like Avro. Which would you choose for storing tokenized LLM training data and why?
#Storage Formats
#Big Data
#I/O Optimization
Data Engineer
•
Technical
•
hard
How does Apache Kafka ensure exactly-once semantics? In what scenarios would you choose at-least-once over exactly-once for Anthropic's data pipelines?
#Kafka
#Distributed Messaging
#Semantics
Data Engineer
•
Technical
•
medium
Explain how you would diagnose and optimize a PySpark job that is failing due to OutOfMemory (OOM) errors caused by severe data skew.
#Spark
#Performance Tuning
#Data Skew
Data Engineer
•
Technical
•
hard
How would you handle backfilling a massive historical dataset (2PB) after a subtle bug is found in the tokenization logic that has been running for 6 months?
#Backfilling
#Data Pipelines
#Idempotency
Data Engineer
•
Technical
•
medium
Explain the differences between at-least-once, at-most-once, and exactly-once delivery semantics in distributed streaming platforms like Kafka. How do you achieve exactly-once processing?
#Kafka
#Streaming
#Distributed Systems
Data Engineer
•
Technical
•
medium
We store petabytes of text data for model training. Compare and contrast storing this data in Parquet, JSONL, and TFRecord/WebDataset formats. Which would you choose for a distributed PyTorch training job and why?
#File Formats
#Storage Optimization
#Machine Learning Infrastructure
Data Scientist
•
Behavioral
•
easy
Describe a time you automated a tedious data process or evaluation pipeline that saved your team significant time.
#Impact
#Automation
#Engineering Best Practices
Data Scientist
•
Behavioral
•
medium
Tell me about a time you had to trade off model performance or project velocity for safety, fairness, or rigorous evaluation.
#AI Safety
#Ethics
#Decision Making
Data Scientist
•
Behavioral
•
medium
Anthropic highly values Constitutional AI. How would you handle a situation where a Product Manager wants to push a feature that significantly increases user engagement but slightly degrades our core alignment metrics?
#Alignment
#Stakeholder Management
#Product Strategy
Data Scientist
•
Behavioral
•
medium
Tell me about a time you discovered a significant flaw in your own data analysis after you had already presented the results to stakeholders. How did you handle it?
#Integrity
#Communication
#Mistakes
Data Scientist
•
Behavioral
•
hard
Anthropic highly values safety. Describe a situation where you had to push back against a product launch or feature because of safety, privacy, or data quality concerns.
#Safety
#Conflict Resolution
#Values
Data Scientist
•
Behavioral
•
easy
Tell me about a time you had to communicate a complex statistical concept to a non-technical stakeholder, such as a policy expert or product manager.
#Communication
#Cross-functional
Data Scientist
•
Behavioral
•
medium
Describe a project where you had to work with highly ambiguous requirements and define the success metrics from scratch.
#Ambiguity
#Initiative
#Metric Design
Data Scientist
•
Behavioral
•
medium
How do you prioritize your research or analysis tasks when faced with multiple urgent requests from different model training and product teams?
#Time Management
#Prioritization
#Stakeholder Management
Data Scientist
•
Behavioral
•
medium
Tell me about a time you disagreed with a senior researcher or engineer about the interpretation of an A/B test result or model evaluation.
#Conflict Resolution
#Data-Driven
#Collaboration
Data Scientist
•
Behavioral
•
easy
Why Anthropic? What specifically about our approach to AI alignment, Constitutional AI, and safety resonates with your career goals?
#Motivation
#Company Knowledge
#Alignment
Data Scientist
•
Behavioral
•
easy
Tell me about a time you had to quickly learn a new machine learning framework, statistical method, or domain to solve a pressing problem.
#Adaptability
#Continuous Learning
#Problem Solving
Data Scientist
•
Behavioral
•
easy
Explain the concept of a p-value and a confidence interval to a non-technical product manager who wants to launch a new feature immediately.
#Statistics
#Stakeholder Management
Data Scientist
•
Behavioral
•
medium
Tell me about a time you had to push back on a product launch or feature release due to data quality or safety concerns.
#Integrity
#Communication
#Conflict Resolution
Data Scientist
•
Behavioral
•
medium
Describe a situation where you discovered a critical flaw in your own analysis after it had already been shared with stakeholders. What did you do?
#Accountability
#Intellectual Honesty
Data Scientist
•
Behavioral
•
medium
How do you prioritize which research directions or metrics to focus on when evaluating open-ended model capabilities?
#Prioritization
#Ambiguity
#Research Strategy
Data Scientist
•
Behavioral
•
easy
Tell me about a time you had to communicate a highly complex statistical or machine learning concept to a group of software engineers.
#Cross-functional Collaboration
#Communication
Data Scientist
•
Behavioral
•
easy
Why do you want to work at Anthropic specifically, as opposed to other AI research labs like OpenAI, DeepMind, or Meta?
#Motivation
#Company Knowledge
Data Scientist
•
Coding
•
medium
Given a table of human evaluations, write a SQL query to find the specific prompts that have the highest variance in human helpfulness ratings (indicating subjective or ambiguous prompts).
#SQL
#Aggregation
#Statistics
Data Scientist
•
Coding
•
medium
Write a SQL query to find the top 5% of users by token usage who have also triggered the safety filter more than 3 times in the last 30 days.
#Window Functions
#Filtering
#Aggregations
Data Scientist
•
Coding
•
easy
Write a SQL query to calculate the 7-day rolling average of API requests per organization.
#Moving Averages
#Window Functions
Data Scientist
•
Coding
•
medium
Write a Python function to compute the BLEU score between a candidate string and a list of reference strings from scratch.
#NLP
#Algorithms
#String Manipulation
Data Scientist
•
Coding
•
medium
Implement an algorithm to perform stratified sampling on a large dataset of RLHF prompts, ensuring equal representation across 10 different safety categories.
#Sampling
#Data Manipulation
#Pandas
Data Scientist
•
Coding
•
hard
Write a Python function to find the longest repeating substring in a generated text. This is useful for detecting if a model has fallen into a repetitive loop.
#Dynamic Programming
#Suffix Trees
#String Algorithms
Data Scientist
•
Coding
•
easy
Given a massive JSONL file of model interaction logs, write a memory-efficient Python script to extract the error rate per model version.
#File I/O
#Memory Management
#JSON
Data Scientist
•
Coding
•
medium
Implement the TF-IDF algorithm from scratch in Python to find the most important keywords in a set of user queries.
#NLP
#Math
#Data Structures
Data Scientist
•
Coding
•
medium
Given a table `claude_generations` with columns `user_id`, `prompt_length`, `generation_time_ms`, and `timestamp`, write a SQL query to calculate the 95th percentile latency for each user tier (join with `users` table) over the last 30 days.
#Window Functions
#Percentiles
#Performance Metrics
Data Scientist
•
Coding
•
medium
Write a Python function to efficiently deduplicate a massive dataset of text documents (billions of tokens) prior to model pre-training. What algorithmic approach would you use?
#Python
#Data Deduplication
#MinHash
#LSH
Data Scientist
•
Coding
•
medium
Implement a function in Python to calculate the Elo rating update for two LLMs given a human preference rating (win, loss, or tie).
#Python
#Math
#Algorithms
Data Scientist
•
Coding
•
hard
Given a table of user prompts with timestamps, write a SQL query to group these prompts into 'sessions'. A new session starts if there is a gap of more than 30 minutes between prompts.
#Sessionization
#Window Functions
#Time Series
Data Scientist
•
Coding
•
medium
Write a SQL query to calculate the week-over-week retention rate of users who interacted with a specific new model version.
#Cohort Analysis
#Retention
#Self Joins
Data Scientist
•
Coding
•
medium
How would you identify potential prompt injection attempts in our logs using a combination of regex and SQL?
#Regex
#Security
#Text Processing
Data Scientist
•
Coding
•
easy
Write a Python function to parse a large JSONL file of Claude's interaction logs and calculate the average response length in tokens for each prompt category.
#Python
#JSON
#Data Processing
Data Scientist
•
Coding
•
medium
Write a SQL query to calculate the rolling 7-day average of human preference win-rates for Claude 3 versus Claude 2, partitioned by the evaluation domain.
#SQL
#Window Functions
#Time Series
Data Scientist
•
Coding
•
hard
Given a dataset of prompt-response pairs with boolean safety violation flags from human annotators and a classifier's probability scores, write a script to compute the ROC-AUC score from scratch.
#Python
#ML Metrics
#Algorithms
Data Scientist
•
Coding
•
medium
Write a SQL query to identify the top 1% most active API users based on token consumption over the last 30 days, excluding internal Anthropic test accounts.
#SQL
#Percentiles
#Filtering
Data Scientist
•
Coding
•
medium
Implement a stratified sampling algorithm to select 10,000 prompt-response pairs for human evaluation, ensuring the sample exactly matches the real-world distribution of 15 different safety categories.
#Python
#Sampling
#Statistics
Data Scientist
•
Coding
•
medium
Write a Python function using NumPy to efficiently compute the cosine similarity between a single target embedding vector and a matrix of 1 million document embeddings.
#Python
#NumPy
#Linear Algebra
Data Scientist
•
Coding
•
medium
Given a table `user_interactions`, write a SQL query to find all users who have triggered the safety filter (`is_blocked = TRUE`) more than 3 times within any rolling 24-hour window.
#Rolling Windows
#Self Joins
#Anomaly Detection
Data Scientist
•
Coding
•
hard
Implement an algorithm to find the longest common substring between two large text prompts. We use this to identify potential prompt injection templates spreading among users.
#Dynamic Programming
#String Manipulation
#Security
Data Scientist
•
Coding
•
easy
Write a Python script using Pandas to sample a stratified subset of 10,000 conversational logs, ensuring a balanced distribution across 5 different safety violation categories, while prioritizing longer conversations.
#Stratified Sampling
#Pandas
#Data Preparation
Data Scientist
•
System Design
•
hard
Design a telemetry and analytics system to monitor Claude's response latency, token generation speed, and output quality in real-time.
#Data Pipelines
#Real-time Analytics
#Monitoring
Data Scientist
•
System Design
•
medium
Design a dashboard and the underlying metrics suite for a new Claude enterprise feature that allows companies to upload their own knowledge bases.
#Metrics Design
#RAG
#B2B Analytics
Data Scientist
•
System Design
•
hard
How would you design a data pipeline to continuously evaluate model drift and degradation over time?
#MLOps
#Model Drift
#Data Engineering
Data Scientist
•
System Design
•
medium
Design an anomaly detection system to identify sudden spikes in API token usage that could indicate a compromised key or a scraping attack.
#Anomaly Detection
#Security
#Time Series
Data Scientist
•
System Design
•
hard
Design an experiment to test whether adding a new principle to Claude's Constitutional AI prompt improves user satisfaction without increasing refusal rates on benign queries.
#A/B Testing
#Constitutional AI
#Metrics
Data Scientist
•
System Design
•
hard
Propose an architecture for storing and querying billions of vector embeddings to support internal retrieval-augmented generation (RAG) experiments.
#Vector Databases
#Search
#Scalability
Data Scientist
•
System Design
•
hard
Design an automated evaluation pipeline (Auto-Eval) that uses a stronger model (e.g., Opus) to grade a weaker model's (e.g., Haiku) outputs. How do you detect and mitigate positional bias and verbosity bias in the evaluator?
#Auto-Evals
#LLM-as-a-Judge
#Bias Mitigation
Data Scientist
•
System Design
•
medium
Design a telemetry and metrics dashboard system to monitor Claude's real-time refusal rates across different API endpoints and customer tiers.
#Data Architecture
#Monitoring
#Streaming
Data Scientist
•
System Design
•
hard
How would you design a data pipeline to ingest, clean, and deduplicate 100TB of web-scraped text for LLM pre-training?
#Big Data
#Data Engineering
#Spark
Data Scientist
•
System Design
•
hard
Design a telemetry and data pipeline system to capture human-in-the-loop feedback (e.g., thumbs up/down, rewritten responses) for RLHF at scale.
#Data Pipelines
#RLHF
#Streaming Data
Data Scientist
•
System Design
•
hard
Design an evaluation system to continuously benchmark Claude against competitor models (like GPT-4) using both automated metrics and human-in-the-loop.
#MLOps
#Evaluation
#Human-in-the-loop
Data Scientist
•
System Design
•
medium
Design a system to track and attribute compute costs (GPU hours) to specific research experiments, model runs, and individual data scientists.
#Data Modeling
#Cloud Infrastructure
#Analytics
Data Scientist
•
Technical
•
hard
How would you use a Bayesian approach to establish an upper bound on the probability of Claude generating a harmful response, given zero observed failures in a sample of 10,000 prompts?
#Bayesian Statistics
#Risk Assessment
Data Scientist
•
Technical
•
medium
Describe a scenario where Simpson's Paradox might occur in our model evaluation data, and how you would resolve it.
#Data Analysis
#Causal Inference
#Probability
Data Scientist
•
Technical
•
medium
If we want to detect a 0.1% increase in severe safety violations (a very rare event), how would you calculate the required sample size for the A/B test?
#A/B Testing
#Sample Size
#Rare Events
Data Scientist
•
Technical
•
medium
How would you detect and quantify data contamination (test set leakage) in our pre-training corpus?
#Data Processing
#NLP
#Model Evaluation
Data Scientist
•
Technical
•
hard
How would you measure the trade-off between helpfulness and harmlessness (the 'HHH' alignment) when evaluating a new model checkpoint?
#AI Safety
#Trade-off Analysis
#Experimentation
Data Scientist
•
Technical
•
medium
Given a dataset of human preference ratings for RLHF, how would you identify and correct for annotator bias or inconsistent grading?
#RLHF
#Data Quality
#Statistical Testing
Data Scientist
•
Technical
•
hard
How would you design an evaluation metric to quantify the rate of subtle hallucinations in Claude's long-form summarization tasks?
#LLM Evaluation
#NLP
#Metrics Design
Data Scientist
•
Technical
•
hard
How would you design an A/B test to evaluate if a new RLHF reward model improves Claude's helpfulness without degrading its safety?
#Experimentation
#RLHF
#Trade-offs
Data Scientist
•
Technical
•
medium
We want to measure the hallucination rate of a new model version. How do you define the metric and design the evaluation pipeline?
#LLM Evaluation
#Metrics
#Data Pipelines
Data Scientist
•
Technical
•
medium
Explain how you would handle Simpson's Paradox if you noticed it while analyzing human feedback data across different demographic groups of annotators.
#Statistics
#Data Analysis
#Bias
Data Scientist
•
Technical
•
medium
How do you determine the required sample size for a human evaluation task where the baseline win rate is 52% and we want to detect a 1% absolute improvement with 95% confidence?
#A/B Testing
#Power Analysis
#Statistics
Data Scientist
•
Technical
•
easy
What statistical test would you use to compare the latency distributions of two different inference engine configurations, given that latency is heavily right-skewed?
#Hypothesis Testing
#Non-parametric Stats
Data Scientist
•
Technical
•
medium
If our automated safety classifier has a false positive rate of 5%, and 1% of all prompts are actually unsafe, what is the probability that a flagged prompt is actually unsafe?
#Bayes Theorem
#Probability
Data Scientist
•
Technical
•
hard
How would you model the relationship between model parameter count, training compute, and downstream zero-shot accuracy to predict the performance of our next-generation model?
#Scaling Laws
#Regression
#Predictive Modeling
Data Scientist
•
Technical
•
hard
Describe how you would detect data contamination (test set leakage) in a massive 5-trillion token pre-training corpus.
#Data Quality
#NLP
#Algorithms
Data Scientist
•
Technical
•
medium
Explain the concept of Constitutional AI. How would you quantitatively measure if a model is adhering to its constitution?
#Constitutional AI
#Alignment
#Metrics
Data Scientist
•
Technical
•
medium
What are the trade-offs between using automated LLM-as-a-judge evaluations versus human annotators for scoring model helpfulness?
#LLM Evaluation
#Bias
#Data Quality
Data Scientist
•
Technical
•
hard
How do you mitigate the 'length bias' (where models or humans prefer longer answers regardless of quality) in RLHF data?
#RLHF
#Bias Mitigation
#Modeling
Data Scientist
•
Technical
•
hard
Explain the difference between PPO (Proximal Policy Optimization) and DPO (Direct Preference Optimization) from a data requirements and modeling perspective.
#RLHF
#DPO
#PPO
Data Scientist
•
Technical
•
medium
How would you evaluate the coding capabilities of an LLM beyond just exact-match pass@k on standard datasets like HumanEval?
#Evaluation
#Code Generation
#Metrics
Data Scientist
•
Technical
•
hard
How would you design a robust evaluation metric to measure hallucination rates in Claude's summarization tasks across different domains (e.g., legal, medical, casual)?
#LLM Evaluation
#Hallucination
#Metrics Design
Data Scientist
•
Technical
•
medium
We recently rolled out a new Constitutional AI principle that makes Claude more harmless, but initial A/B tests show a 5% drop in user retention. How do you analyze this trade-off and what is your recommendation?
#A/B Testing
#Trade-off Analysis
#Product Analytics
Data Scientist
•
Technical
•
hard
You notice that Claude 3 Opus performs better overall on a benchmark than Claude 3 Sonnet, but when you break the data down by language (English, Spanish, Mandarin), Sonnet outperforms Opus in every single category. Explain how this is statistically possible.
#Simpson's Paradox
#Data Analysis
#Confounding Variables
Data Scientist
•
Technical
•
hard
From a data distribution and statistical perspective, explain the differences between preparing preference data for Direct Preference Optimization (DPO) versus traditional RLHF (PPO).
#RLHF
#DPO
#Preference Data
Data Scientist
•
Technical
•
medium
How would you determine the required sample size for human annotators grading Claude's helpfulness to achieve statistical significance, given historically high variance in inter-rater reliability?
#Sample Size Calculation
#Inter-rater Reliability
#Hypothesis Testing
Data Scientist
•
Technical
•
hard
How do you detect and mitigate data contamination (test set leakage) in the massive pre-training corpus of a large language model to ensure our benchmark scores are valid?
#Data Contamination
#Test Leakage
#Pre-training Data
Data Scientist
•
Technical
•
hard
How would you estimate the causal impact of a new Constitutional AI principle on long-term user retention, given that we cannot run a perfectly randomized control trial for months?
#Causal Inference
#Observational Data
#Retention
Data Scientist
•
Technical
•
medium
Explain how you would cluster millions of unstructured user prompts to identify emerging use cases and feature requests.
#Unsupervised Learning
#NLP
#Clustering
Data Scientist
•
Technical
•
hard
What are the primary limitations and biases of using strong LLMs as judges for evaluating the outputs of other LLMs?
#LLM Evaluation
#Bias
#Research Methodology
Data Scientist
•
Technical
•
medium
How do you handle severe class imbalance when training a classifier to detect rare jailbreak attempts in user prompts?
#Classification
#Imbalanced Data
#Security
Data Scientist
•
Technical
•
hard
Explain the mathematics and intuition behind Proximal Policy Optimization (PPO) at a high level, and why it is preferred for RLHF.
#Reinforcement Learning
#Math
#RLHF
Data Scientist
•
Technical
•
medium
Formulate a composite metric to capture 'user frustration' during a multi-turn chat with Claude.
#User Behavior
#Metrics Design
#NLP
DevOps Engineer
•
Behavioral
•
medium
Tell me about a time you strongly disagreed with a technical decision made by a senior engineer or researcher. How did you resolve it?
#Communication
#Conflict Resolution
#Collaboration
DevOps Engineer
•
Behavioral
•
medium
Tell me about a time you had to learn a completely new technology under immense pressure to solve a critical production issue.
#Adaptability
#Problem Solving
#Stress Management
DevOps Engineer
•
Behavioral
•
medium
Tell me about a time you had to balance rapid iteration and deployment speed with strict security and reliability requirements. How did you handle the trade-offs?
#Security
#Agile
#Decision Making
DevOps Engineer
•
Behavioral
•
easy
Describe a time you automated yourself out of a job or significantly reduced operational toil for your team.
#Automation
#Impact
#Initiative
DevOps Engineer
•
Behavioral
•
easy
Why do you want to work at Anthropic specifically? How do your engineering values align with our focus on AI safety and reliability?
#Motivation
#Company Values
#AI Safety
DevOps Engineer
•
Behavioral
•
medium
You receive a PagerDuty alert at 2 AM that API latency has spiked by 400%. Walk me through your incident response and triage process.
#SRE
#Troubleshooting
#Communication
DevOps Engineer
•
Coding
•
medium
Implement a basic rate limiter class in Python or Go using the Token Bucket algorithm.
#Concurrency
#Algorithms
#System Design
DevOps Engineer
•
Coding
•
medium
Write a Go or Python program to interact with the AWS EC2 API, find all orphaned EBS volumes (status 'available'), and delete them if they haven't been attached in the last 30 days.
#API Integration
#AWS
#Cost Optimization
#Coding
DevOps Engineer
•
Coding
•
medium
Write a script to recursively traverse a directory, calculate the SHA-256 hash of all files, and output a list of duplicate files.
#File System
#Hashing
#Python/Bash
DevOps Engineer
•
Coding
•
hard
Given a list of overlapping IP CIDR blocks, write a function to merge them into the minimum number of non-overlapping CIDR blocks.
#Networking
#Algorithms
#Intervals
DevOps Engineer
•
Coding
•
easy
Write a function to implement a basic Round Robin load balancer. It should take a list of servers and return the next server to route a request to.
#Load Balancing
#Data Structures
DevOps Engineer
•
Coding
•
medium
Write a bash or Python script that continuously monitors a specific process by PID and alerts if its memory usage exceeds a certain threshold for more than 5 minutes.
#Linux
#Process Management
#Monitoring
DevOps Engineer
•
Coding
•
easy
Write a script to validate a complex JSON configuration file against a predefined JSON schema, and output human-readable error messages for any validation failures.
#JSON
#Validation
#Automation
DevOps Engineer
•
Coding
•
medium
Write a Python script to parse a large stream of application logs, identify rate-limited requests (HTTP 429), and output the top 5 offending API keys.
#Python
#Log Parsing
#Data Structures
DevOps Engineer
•
System Design
•
hard
You are tasked with migrating a critical, high-traffic service from AWS to GCP. How do you plan and execute this migration with zero downtime?
#Cloud Migration
#Networking
#Databases
DevOps Engineer
•
System Design
•
hard
Design a system to securely ingest, sanitize, and store petabytes of training data from external sources.
#Data Engineering
#Security
#Storage
#Scale
DevOps Engineer
•
System Design
•
hard
Design a highly available, secure egress proxy architecture for our internal VPCs to ensure outbound traffic is strictly filtered and logged.
#Networking
#Security
#AWS/GCP
DevOps Engineer
•
System Design
•
hard
How would you design an observability stack to monitor the health and performance of thousands of distributed GPU training jobs?
#Observability
#Prometheus
#Grafana
#Distributed Systems
DevOps Engineer
•
System Design
•
hard
Design a CI/CD pipeline for a massive monorepo containing both ML model weights and application code. How do you optimize build and deployment times?
#CI/CD
#Monorepo
#Performance Optimization
DevOps Engineer
•
System Design
•
hard
Describe how you would structure a Terraform repository for a rapidly growing infrastructure team managing multiple environments (Dev, Staging, Prod) across multiple cloud regions.
#Terraform
#Architecture
#State Management
DevOps Engineer
•
System Design
•
hard
How would you design a multi-tenant Kubernetes cluster for our AI researchers, ensuring strict network isolation and resource quotas between different research teams?
#Kubernetes
#Security
#Networking
#Multi-tenancy
DevOps Engineer
•
System Design
•
hard
Design the infrastructure for serving a large language model like Claude, ensuring high availability, low latency, and efficient GPU utilization.
#Infrastructure
#GPU Provisioning
#High Availability
#Load Balancing
DevOps Engineer
•
System Design
•
medium
Design a GitOps workflow using ArgoCD or Flux for deploying microservices. How do you handle environment promotion (Dev -> Staging -> Prod)?
#GitOps
#CI/CD
#Kubernetes
DevOps Engineer
•
Technical
•
medium
How do you handle Terraform state drift? Describe a mechanism you would build to automatically detect and remediate manual changes made in the AWS console.
#Terraform
#Automation
#Compliance
DevOps Engineer
•
Technical
•
medium
You notice a Kubernetes pod running a critical ML inference workload is stuck in a CrashLoopBackOff state. Walk me through your exact troubleshooting steps.
#Kubernetes
#Debugging
#Containers
DevOps Engineer
•
Technical
•
hard
We use AWS IAM extensively. Explain how IAM Role assumption works, and how you would prevent the 'confused deputy' problem in a cross-account setup.
#AWS
#IAM
#Security
DevOps Engineer
•
Technical
•
medium
How do you handle database schema migrations in a fully automated CI/CD pipeline without causing locks or downtime?
#CI/CD
#Databases
#Automation
DevOps Engineer
•
Technical
•
medium
Explain how DNS resolution works. If an internal service in a VPC cannot resolve an external domain, what specific steps do you take to debug?
#DNS
#Troubleshooting
#Networking
DevOps Engineer
•
Technical
•
medium
How would you optimize Docker image build times and reduce the final image size for a Python-based ML application with heavy dependencies like PyTorch?
#Docker
#Optimization
#CI/CD
DevOps Engineer
•
Technical
•
medium
Explain the Linux boot process from the moment a server is powered on to when the user login prompt appears.
#OS Fundamentals
#Linux
DevOps Engineer
•
Technical
•
hard
We need to upgrade our production Kubernetes cluster to a new minor version. Walk me through your strategy to achieve this with zero downtime for our API users.
#Kubernetes
#Upgrades
#Zero Downtime
DevOps Engineer
•
Technical
•
easy
Explain the difference between a Kubernetes Deployment and a StatefulSet. In what scenario involving ML infrastructure would you strictly require a StatefulSet?
#Kubernetes
#State Management
DevOps Engineer
•
Technical
•
medium
Anthropic places a heavy emphasis on security. How would you securely manage and inject secrets into a CI/CD pipeline deploying to AWS/GCP without hardcoding them?
#CI/CD
#Secrets Management
#IAM
DevOps Engineer
•
Technical
•
medium
What are SLIs, SLOs, and SLAs? How would you define them for a user-facing LLM inference API?
#SRE
#Metrics
#Reliability
DevOps Engineer
•
Technical
•
hard
What is a Kubernetes Mutating Admission Webhook? Give an example of how you would use it to enforce security policies at Anthropic.
#Kubernetes
#Security
#Extensibility
Frontend Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a senior engineer or product manager on an architectural or product decision. How was it resolved?
#Conflict Resolution
#Communication
#Technical Leadership
Frontend Engineer
•
Behavioral
•
medium
How do you balance the need to ship features quickly with the requirement to write rigorous, highly reliable, and safe code?
#Prioritization
#Engineering Excellence
#Trade-offs
Frontend Engineer
•
Behavioral
•
medium
Describe a time you had to collaborate closely with researchers, data scientists, or non-engineering stakeholders to deliver a feature.
#Cross-functional
#Communication
#Empathy
Frontend Engineer
•
Behavioral
•
easy
Why Anthropic? What specifically draws you to our mission of building reliable, interpretable, and steerable AI systems compared to other companies in this space?
#Motivation
#Company Knowledge
#Alignment
Frontend Engineer
•
Behavioral
•
medium
Tell me about a time you had to push back on a product feature or deadline because of safety, security, or reliability concerns.
#Communication
#Safety
#Prioritization
Frontend Engineer
•
Behavioral
•
easy
Describe a situation where you had to learn a complex new technology or domain quickly to complete a project.
#Adaptability
#Learning
#Curiosity
Frontend Engineer
•
Behavioral
•
easy
Anthropic values 'helpful, honest, and harmless' AI. How do you think these principles apply to the work of a Frontend Engineer?
#Values
#Product Thinking
#Ethics
Frontend Engineer
•
Behavioral
•
medium
Tell me about a time you discovered a critical bug or security vulnerability in production. How did you handle it?
#Incident Management
#Problem Solving
#Accountability
Frontend Engineer
•
Coding
•
hard
Implement a virtualized list component from scratch to render a chat history with thousands of messages of variable heights.
#React
#Virtualization
#Performance
#DOM
Frontend Engineer
•
Coding
•
easy
Write a function that takes a deeply nested JSON object representing an AI's structured output and flattens it into a single-level object with dot-notation keys.
#JavaScript
#Recursion
#Object Manipulation
Frontend Engineer
•
Coding
•
medium
Implement a custom tooltip component in React that dynamically positions itself (top, bottom, left, right) to avoid clipping outside the viewport.
#React
#DOM Measurements
#CSS
#Positioning
Frontend Engineer
•
Coding
•
easy
Implement a rate-limiter utility on the frontend to prevent a user from accidentally spamming the 'Generate' button and exhausting their API quota.
#JavaScript
#Throttling
#UX
Frontend Engineer
•
Coding
•
medium
Write a utility function to deeply merge two complex JavaScript objects, handling arrays and nested objects appropriately.
#JavaScript
#Recursion
#Data Structures
Frontend Engineer
•
Coding
•
medium
Implement a custom hook `useLocalStorage` that syncs state across multiple browser tabs in real-time.
#React Hooks
#Web Storage API
#Event Listeners
Frontend Engineer
•
Coding
•
medium
Build a multi-step configuration form for fine-tuning an AI model. The form has complex validation rules where options in Step 3 depend on selections in Step 1.
#React
#Forms
#State Management
#Validation
Frontend Engineer
•
Coding
•
medium
Implement a robust retry mechanism with exponential backoff for a fetch request that calls an unreliable LLM inference API.
#Asynchronous JavaScript
#Promises
#Error Handling
Frontend Engineer
•
Coding
•
hard
Implement a diff viewer component that takes two strings (e.g., an original prompt and an AI-edited prompt) and highlights the insertions and deletions.
#String Manipulation
#Dynamic Programming
#React
Frontend Engineer
•
Coding
•
easy
Write a custom React hook `useDebounce` and use it to implement a search input that queries an API for prompt templates.
#React Hooks
#Debouncing
#API Integration
Frontend Engineer
•
Coding
•
medium
Implement an auto-scrolling mechanism for a chat interface that stays pinned to the bottom as new tokens arrive, but stops auto-scrolling if the user scrolls up to read previous messages.
#React
#DOM APIs
#Scroll Events
#UX
Frontend Engineer
•
Coding
•
medium
Write a function to parse and safely render Markdown generated by an LLM. How do you ensure the output is protected against Cross-Site Scripting (XSS) attacks?
#Markdown
#XSS
#Sanitization
#DOM Manipulation
Frontend Engineer
•
Coding
•
medium
Implement a React component that consumes a Server-Sent Events (SSE) endpoint to stream and render text token by token, similar to Claude's chat interface.
#React
#Server-Sent Events
#Streaming
#State Management
Frontend Engineer
•
System Design
•
hard
Design a real-time collaborative prompt engineering playground where multiple users can edit a prompt and see model outputs simultaneously.
#CRDTs
#WebSockets
#Collaboration
#Concurrency
Frontend Engineer
•
System Design
•
hard
Design an internal data labeling and evaluation tool for RLHF (Reinforcement Learning from Human Feedback). The tool needs to display two model outputs side-by-side and allow researchers to annotate specific spans of text.
#UX/UI
#Data Handling
#Component Design
#Internal Tools
Frontend Engineer
•
System Design
•
hard
Design the frontend architecture for the Claude web application. Focus on state management for chat histories, handling real-time streaming responses, and offline capabilities.
#Architecture
#State Management
#Real-time
#Offline Storage
Frontend Engineer
•
System Design
•
hard
Design the frontend for a model evaluation dashboard that needs to render charts and tables for millions of data points efficiently.
#Data Visualization
#Web Workers
#Canvas/WebGL
#Pagination
Frontend Engineer
•
System Design
•
medium
Design a telemetry and error tracking system for the frontend that helps engineers debug issues without capturing or logging sensitive user prompts or PII.
#Observability
#Privacy
#Error Handling
Frontend Engineer
•
System Design
•
medium
Design a system to handle file uploads (e.g., large PDFs or datasets) from the client to the server for Claude to analyze, including progress indicators and resumable uploads.
#File Uploads
#Chunking
#UX
#Network
Frontend Engineer
•
System Design
•
medium
Design a robust frontend caching layer for LLM responses to avoid redundant API calls when a user navigates back and forth through their chat history.
#Caching
#State Management
#Performance
Frontend Engineer
•
Technical
•
hard
What are the security implications of rendering user-uploaded files (e.g., PDFs, images) in the browser, and how do you mitigate them?
#File Uploads
#CORS
#CSP
#Browser Security
Frontend Engineer
•
Technical
•
medium
Explain the differences between WebSockets, Server-Sent Events (SSE), and Long Polling. Which would you choose for streaming AI responses and why?
#Protocols
#Streaming
#WebSockets
#SSE
Frontend Engineer
•
Technical
•
hard
How would you optimize a React application that experiences severe UI lag when rendering a very long, continuously streaming AI response?
#React Profiler
#Memoization
#Rendering Optimization
#Concurrency
Frontend Engineer
•
Technical
•
medium
Explain how the browser's Event Loop works. How does it handle microtasks (Promises) versus macrotasks (setTimeout), and why does this matter for UI rendering?
#JavaScript Engine
#Event Loop
#Asynchronous JavaScript
Frontend Engineer
•
Technical
•
medium
How do you handle memory leaks in a modern Single Page Application (SPA)? Walk me through your debugging process.
#Memory Management
#Chrome DevTools
#Closures
#Event Listeners
Frontend Engineer
•
Technical
•
medium
Explain how you would test a non-deterministic UI, such as a chat interface where the AI's response varies slightly every time.
#E2E Testing
#Mocking
#Flaky Tests
#UI Testing
Frontend Engineer
•
Technical
•
medium
How do you ensure a highly dynamic chat interface, where content is constantly streaming and updating, remains fully accessible to screen reader users?
#a11y
#ARIA
#Screen Readers
#Dynamic Content
Full Stack Engineer
•
Behavioral
•
medium
Anthropic places a heavy emphasis on Constitutional AI and alignment. How do you approach building user interfaces or product features where the underlying model's behavior might be non-deterministic or unpredictable?
#UX Design
#Ambiguity
#AI Integration
Full Stack Engineer
•
Behavioral
•
medium
Tell me about a time you had to dive deep into a completely unfamiliar part of the stack or a new technology to debug a critical production issue.
#Debugging
#Adaptability
#Learning
Full Stack Engineer
•
Behavioral
•
medium
What is your approach to writing automated tests for non-deterministic systems, such as user interfaces that depend on generative LLM outputs?
#Testing
#Mocks
#Non-determinism
Full Stack Engineer
•
Behavioral
•
easy
Tell me about a time you mentored a junior engineer or helped a non-technical team member understand a highly complex technical concept.
#Mentorship
#Communication
#Empathy
Full Stack Engineer
•
Behavioral
•
medium
How do you prioritize your engineering tasks when working in an environment where sudden AI research breakthroughs can drastically change product roadmaps overnight?
#Adaptability
#Agile
#Prioritization
Full Stack Engineer
•
Behavioral
•
medium
Tell me about a time you had to balance shipping a feature quickly versus ensuring it met strict safety, security, or quality standards. How did you navigate the trade-off?
#Safety
#Prioritization
#Decision Making
Full Stack Engineer
•
Behavioral
•
hard
Give an example of a time you identified a fundamental flaw in a system's architecture. How did you advocate for fixing it, and what was the outcome?
#Architecture
#Advocacy
#Impact
Full Stack Engineer
•
Behavioral
•
medium
Describe a situation where you disagreed with a researcher, data scientist, or product manager on how to implement a feature. How did you resolve the disagreement?
#Conflict Resolution
#Communication
#Cross-functional
Full Stack Engineer
•
Coding
•
medium
Given a massive log file of API requests, write a Python script to find the top 5 users who consumed the most tokens in any sliding 1-hour window.
#Python
#Sliding Window
#Data Processing
Full Stack Engineer
•
Coding
•
medium
Write a function to merge overlapping text highlights. Given an array of objects representing start and end indices of safety flags in a text, return a merged array of non-overlapping intervals.
#Intervals
#Sorting
#Arrays
Full Stack Engineer
•
Coding
•
medium
Implement an LRU (Least Recently Used) cache with a Time-To-Live (TTL) feature to temporarily store frequent, identical prompt responses and reduce inference load.
#Data Structures
#Caching
#Hash Maps
#Linked Lists
Full Stack Engineer
•
Coding
•
hard
Implement a custom JSON parser that can gracefully handle and 'fix' truncated JSON strings. This is common when an LLM output stops mid-generation due to max token limits.
#Parsing
#Strings
#Error Handling
#AST
Full Stack Engineer
•
Coding
•
hard
Write an algorithm to efficiently diff two versions of a large text document and highlight the insertions and deletions. This is used to show users how their prompt edits changed the context.
#Dynamic Programming
#Strings
#Diff Algorithms
Full Stack Engineer
•
Coding
•
medium
Write a function to recursively traverse a DOM tree and extract its text content while maintaining semantic spacing (e.g., adding line breaks for block elements like <p> or <div>).
#DOM
#Recursion
#Trees
Full Stack Engineer
•
Coding
•
medium
Implement a React component that consumes a Server-Sent Events (SSE) endpoint to display a streaming text response from an LLM. It must gracefully handle connection drops and auto-scroll to the bottom as new text arrives.
#React
#SSE
#Streaming
#DOM Manipulation
Full Stack Engineer
•
Coding
•
hard
Write a rate limiter middleware in Node.js/TypeScript using Redis. Unlike standard rate limiters, this must limit based on the number of 'tokens' consumed, which is only known *after* the API request completes.
#Node.js
#Redis
#Concurrency
#API Design
Full Stack Engineer
•
Coding
•
medium
Build a custom React hook `useChat` that manages message state, handles loading states, and provides a function to abort an ongoing LLM generation using AbortController.
#React Hooks
#State Management
#Fetch API
#AbortController
Full Stack Engineer
•
Coding
•
medium
Implement a debounce function that delays invoking a function until after `wait` milliseconds, but also guarantees execution at least once every `maxWait` milliseconds (useful for auto-saving chat drafts).
#JavaScript
#Timers
#Closures
Full Stack Engineer
•
Coding
•
medium
Implement a concurrent task scheduler in Node.js that takes an array of asynchronous tasks and limits the number of active API requests to an external service to exactly `N`.
#Concurrency
#Promises
#Node.js
Full Stack Engineer
•
Coding
•
hard
Implement a Markdown parser function in TypeScript that can render code blocks with syntax highlighting *while* the text is still streaming in chunk by chunk.
#Parsing
#TypeScript
#Streaming
#State Machines
Full Stack Engineer
•
System Design
•
hard
Design a telemetry and logging system for LLM outputs that allows researchers to query for safety violations or model hallucinations, without compromising user privacy or storing PII.
#Privacy
#Data Pipelines
#Security
#Analytics
Full Stack Engineer
•
System Design
•
hard
Design a system to handle prompt injection detection. This system must evaluate user input before it reaches the core LLM inference engine, adding no more than 50ms of latency.
#Security
#Low Latency
#Microservices
#Machine Learning
Full Stack Engineer
•
System Design
•
hard
Design a usage billing system for an LLM API that charges based on both input and output tokens. It must handle millions of requests per minute and ensure customers are never overcharged.
#Billing
#Distributed Systems
#Event Sourcing
#Idempotency
Full Stack Engineer
•
System Design
•
hard
Design a scalable document ingestion pipeline that extracts text from user-uploaded PDFs, chunks it, generates embeddings, and stores it in a vector database for RAG.
#Pipelines
#Vector Databases
#Asynchronous Processing
#RAG
Full Stack Engineer
•
System Design
•
medium
Design an internal annotation tool for researchers to rate and compare model responses (RLHF). It needs to handle concurrent edits, offline support, and high data integrity.
#Internal Tools
#Offline First
#Concurrency
#Data Integrity
Full Stack Engineer
•
System Design
•
hard
Design a system for users to upload, manage, and query against their own custom datasets (up to 10GB per user) within a chat interface. How do you ensure isolation and fast retrieval?
#Multi-tenancy
#Storage
#Search
#Security
Full Stack Engineer
•
System Design
•
hard
Design the backend architecture for Claude's chat interface. Focus specifically on how you would handle low-latency streaming of tokens to the client while simultaneously persisting the conversation history to a database.
#Architecture
#Streaming
#Database Design
#Concurrency
Full Stack Engineer
•
System Design
•
hard
Design a distributed queue system to manage LLM inference requests. It must prioritize paid tier users over free tier users during high load, while preventing free tier starvation.
#Queueing Theory
#Distributed Systems
#Fairness
#Load Balancing
Full Stack Engineer
•
System Design
•
hard
Design an A/B testing framework specifically for evaluating different versions of an LLM prompt or model weights in production, measuring both user engagement and safety metrics.
#Experimentation
#Analytics
#Routing
#Data Engineering
Full Stack Engineer
•
Technical
•
hard
How do you optimize a frontend application to handle rendering massive DOMs, such as displaying a 100,000-word context window in a chat UI without freezing the browser?
#Performance
#Virtualization
#DOM
#Web Workers
Full Stack Engineer
•
Technical
•
easy
Discuss the trade-offs between using Server-Sent Events (SSE), WebSockets, and long-polling for streaming LLM responses to a web client.
#Protocols
#Streaming
#Web Architecture
Full Stack Engineer
•
Technical
•
medium
Explain how you would handle WebSocket connection drops and state reconciliation in a real-time collaborative prompt-engineering application.
#WebSockets
#State Management
#CRDTs/OT
Full Stack Engineer
•
Technical
•
medium
How would you secure an internal dashboard that interacts with sensitive model training data and allows researchers to trigger fine-tuning jobs?
#Authentication
#Authorization
#Audit Logging
#Network Security
Full Stack Engineer
•
Technical
•
medium
How would you design a database schema to efficiently store and retrieve multi-turn chat conversations that support branching (e.g., when a user edits a previous prompt and generates a new response path)?
#SQL
#Data Modeling
#Trees/Graphs
Full Stack Engineer
•
Technical
•
medium
Explain how you would implement optimistic UI updates for a chat application where the server validation (e.g., a safety filter) might occasionally fail and reject the message.
#UX
#State Management
#Error Handling
Machine Learning Engineer
•
Behavioral
•
medium
Anthropic highly values 'helpful, honest, and harmless' (HHH) models. Describe a situation where these three traits conflicted in a project you worked on.
#HHH
#Alignment
#Trade-offs
Machine Learning Engineer
•
Behavioral
•
medium
Anthropic places a high value on AI safety. Describe a time you identified a potential negative impact or safety flaw in your work and how you addressed it.
#AI Safety
#Ethics
#Proactivity
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you strongly disagreed with a fellow researcher or engineer on the direction of a model architecture or training pipeline.
#Conflict Resolution
#Collaboration
#Communication
Machine Learning Engineer
•
Behavioral
•
medium
Describe a situation where you had to debug a silent failure (e.g., loss not converging, degraded outputs) in a complex machine learning pipeline.
#Debugging
#Machine Learning
#Problem Solving
Machine Learning Engineer
•
Behavioral
•
medium
How do you prioritize research ideas when working on an open-ended problem like hallucination reduction in LLMs?
#Research Strategy
#Prioritization
#Innovation
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to optimize a piece of code that was bottlenecking a critical ML pipeline or training run.
#Performance Optimization
#Profiling
#Engineering
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to trade off model performance (e.g., accuracy or helpfulness) for safety, fairness, or alignment.
#AI Safety
#Ethics
#Decision Making
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to delay a model release or feature because of a safety, bias, or alignment concern.
#AI Safety
#Ethics
#Decision Making
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time a research experiment or model training run failed completely. How did you pivot and what did you learn?
#Resilience
#Debugging
#Research
Machine Learning Engineer
•
Behavioral
•
medium
How do you balance the pressure to ship capabilities quickly with the need for rigorous safety testing and alignment?
#Prioritization
#Safety vs Capabilities
#Communication
Machine Learning Engineer
•
Behavioral
•
medium
Describe a time when you strongly disagreed with a senior researcher or engineer about the technical direction of an ML project. How was it resolved?
#Conflict Resolution
#Collaboration
#Ego
Machine Learning Engineer
•
Behavioral
•
easy
Anthropic places a heavy emphasis on AI safety. Why do you want to work in AI alignment, and what do you think is the biggest unsolved problem in the field today?
#AI Safety
#Motivation
#Alignment
#Industry Trends
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a trade-off between model performance (e.g., accuracy or helpfulness) and model safety or fairness. How did you approach the decision?
#Safety
#Ethics
#Trade-offs
#Decision Making
Machine Learning Engineer
•
Coding
•
medium
Implement dropout during both the forward and backward pass from scratch using NumPy.
#NumPy
#Backpropagation
#Regularization
Machine Learning Engineer
•
Coding
•
medium
Given a massive log file of model training loss, write a script to detect loss spikes and automatically identify the corrupted data batch.
#Python
#Log Parsing
#Anomaly Detection
Machine Learning Engineer
•
Coding
•
hard
Implement a memory-efficient Ring Attention mechanism to handle extremely long context windows across multiple GPUs.
#Distributed Computing
#Attention
#Memory Optimization
Machine Learning Engineer
•
Coding
•
hard
Implement a custom PyTorch autograd function for a novel activation function, including both the forward and backward passes.
#PyTorch Internals
#Calculus
#Autograd
Machine Learning Engineer
•
Coding
•
medium
Implement a multi-head self-attention mechanism from scratch in PyTorch, ensuring it is highly optimized for batch processing.
#PyTorch
#Transformers
#Linear Algebra
Machine Learning Engineer
•
Coding
•
hard
Implement the forward pass of a Mixture of Experts (MoE) layer with a top-2 routing mechanism.
#MoE
#PyTorch
#Routing
Machine Learning Engineer
•
Coding
•
hard
Implement multi-head self-attention from scratch using PyTorch, including an optional causal mask.
#PyTorch
#Transformers
#Attention Mechanism
Machine Learning Engineer
•
Coding
•
hard
Implement a multi-head self-attention mechanism from scratch in PyTorch. Ensure your implementation efficiently handles batched inputs and causal masking.
#PyTorch
#Transformers
#Attention Mechanism
#Vectorization
Machine Learning Engineer
•
Coding
•
medium
Write an algorithm to find the longest common substring between two large text documents efficiently.
#Dynamic Programming
#Strings
#Suffix Trees
Machine Learning Engineer
•
Coding
•
easy
Implement a sliding window attention mask generator for a sequence of length N and window size W.
#Matrix Operations
#Attention
#PyTorch
Machine Learning Engineer
•
Coding
•
hard
Given a sequence of characters and a vocabulary of merges, implement the Byte-Pair Encoding (BPE) tokenization merging algorithm.
#Tokenization
#NLP
#Greedy Algorithms
Machine Learning Engineer
•
Coding
•
medium
Implement a distributed all-reduce operation using a ring topology. You can write pseudo-code assuming basic send() and recv() primitives.
#Networking
#All-reduce
#Algorithms
#Parallel Computing
Machine Learning Engineer
•
Coding
•
medium
Write a Python function to sample from a logits distribution using top-k and top-p (nucleus) sampling.
#Sampling
#Probability
#PyTorch
Machine Learning Engineer
•
Coding
•
medium
Implement a Trie data structure to efficiently filter out a large list of toxic words from a continuous stream of generated tokens.
#Data Structures
#Trie
#String Manipulation
Machine Learning Engineer
•
Coding
•
medium
Write an algorithm to efficiently sample from a logits distribution using Top-K and Top-P (Nucleus) sampling.
#Probability
#Sampling
#Sorting
Machine Learning Engineer
•
Coding
•
medium
Implement a basic tokenizer using Byte-Pair Encoding (BPE) given a corpus of text and a target vocabulary size.
#NLP
#Tokenization
#String Processing
Machine Learning Engineer
•
Coding
•
medium
Write a Python script using multiprocessing to efficiently tokenize and shard a massive JSONL dataset into binary memmap files.
#Multiprocessing
#I/O
#Tokenization
Machine Learning Engineer
•
Coding
•
easy
Given a string representing a mathematical expression, write a tokenizer that converts it into a list of valid tokens (numbers, operators, parentheses). Handle multi-digit numbers and ignore whitespace.
#Tokenization
#Parsing
#Strings
#State Machines
Machine Learning Engineer
•
Coding
•
medium
Write a Python function to efficiently perform top-k and nucleus (top-p) sampling given a 1D tensor of logits.
#Sampling
#Inference
#Probability
#PyTorch
Machine Learning Engineer
•
Coding
•
medium
Write a PyTorch script to implement simple data parallelism using DistributedDataParallel (DDP), including the setup of the process group.
#PyTorch
#DDP
#Multiprocessing
Machine Learning Engineer
•
Coding
•
medium
Write a PyTorch custom autograd function (subclassing torch.autograd.Function) for a novel activation function, implementing both forward and backward passes.
#PyTorch
#Autograd
#Calculus
Machine Learning Engineer
•
Coding
•
medium
Given a stream of generated tokens, write a highly optimized Trie-based data structure to filter out a dynamic list of toxic phrases in real-time.
#Data Structures
#Trie
#Streaming
Machine Learning Engineer
•
Coding
•
hard
Write a function to perform Rotary Positional Embeddings (RoPE) on a given query and key tensor.
#PyTorch
#Transformers
#Positional Encodings
Machine Learning Engineer
•
System Design
•
hard
How would you architect an API rate-limiting and dynamic batching system for Claude to maximize GPU utilization while guaranteeing latency SLAs?
#API Design
#Dynamic Batching
#Concurrency
Machine Learning Engineer
•
System Design
•
medium
Design an inference API for a large language model. Focus specifically on how you would handle continuous batching and manage the KV-cache efficiently to maximize throughput.
#Inference
#Continuous Batching
#KV Cache
#PagedAttention
Machine Learning Engineer
•
System Design
•
hard
Design a distributed training system for a 100B+ parameter model across 1000 GPUs. How do you handle network topology and parallelism strategies?
#Distributed Training
#Networking
#Parallelism
Machine Learning Engineer
•
System Design
•
medium
Design a red-teaming platform that automatically generates adversarial prompts to test Claude's safety boundaries.
#Red Teaming
#Adversarial ML
#Evaluation
Machine Learning Engineer
•
System Design
•
hard
Design a distributed training system for a 100B+ parameter language model. How would you partition the model across GPUs using tensor, pipeline, and data parallelism?
#Distributed Training
#3D Parallelism
#GPU Architecture
#Megatron-LM
Machine Learning Engineer
•
System Design
•
medium
Design a continuous evaluation system that benchmarks daily model checkpoints against a suite of 50+ reasoning, coding, and safety tasks.
#Evaluation
#CI/CD for ML
#Orchestration
Machine Learning Engineer
•
System Design
•
hard
Design a system to continuously evaluate a production LLM for red-teaming vulnerabilities and prompt injection attacks.
#Red Teaming
#Security
#Evaluation Pipelines
Machine Learning Engineer
•
System Design
•
hard
Design a fault-tolerant checkpointing system for a massive training run that minimizes GPU idle time during saves.
#Checkpointing
#I/O Optimization
#Fault Tolerance
Machine Learning Engineer
•
System Design
•
hard
How would you design the distributed training pipeline for a 100B+ parameter model across 10,000 GPUs?
#Distributed Training
#Megatron-LM
#DeepSpeed
#Network Topology
Machine Learning Engineer
•
System Design
•
hard
Design a reward modeling pipeline to penalize evasive answers (e.g., 'As an AI...') while maintaining the model's helpfulness and harmlessness.
#Reward Modeling
#Alignment
#Data Pipeline
Machine Learning Engineer
•
System Design
•
hard
Design a data pipeline to process and filter petabytes of web-scraped text for pre-training a foundational LLM. How do you handle exact and fuzzy deduplication at this scale?
#Data Pipeline
#Deduplication
#MinHash
#Big Data
Machine Learning Engineer
•
System Design
•
hard
Design a data pipeline to deduplicate, filter, and tokenize a multi-terabyte web scraping dataset for LLM pretraining.
#Data Engineering
#Big Data
#MinHash
#Pretraining
Machine Learning Engineer
•
System Design
•
hard
Design an inference system for Claude that can efficiently handle 100k+ token context windows while serving thousands of concurrent users.
#LLM Serving
#KV Caching
#PagedAttention
#Dynamic Batching
Machine Learning Engineer
•
System Design
•
hard
Design a data deduplication pipeline for a 5-trillion token pretraining dataset.
#Big Data
#MinHash
#LSH
#Distributed Processing
Machine Learning Engineer
•
System Design
•
hard
Design an inference API for a model like Claude that handles high concurrency, minimizes Time to First Token (TTFT), and maximizes throughput.
#API Design
#Inference
#Batching
#Latency
Machine Learning Engineer
•
Technical
•
hard
How would you implement speculative decoding to speed up autoregressive inference? What are the requirements for the draft model?
#Speculative Decoding
#Latency Optimization
#Algorithms
Machine Learning Engineer
•
Technical
•
hard
Discuss the trade-offs between Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ) for deploying a large language model. How do techniques like AWQ or GPTQ mitigate performance degradation?
#Quantization
#Model Compression
#Inference
#AWQ/GPTQ
Machine Learning Engineer
•
Technical
•
hard
Explain the Proximal Policy Optimization (PPO) algorithm used in RLHF. What are its common failure modes in language model fine-tuning?
#PPO
#RLHF
#Optimization
Machine Learning Engineer
•
Technical
•
medium
How does Constitutional AI differ from standard Reinforcement Learning from Human Feedback (RLHF)?
#Constitutional AI
#RLHF
#Alignment
Machine Learning Engineer
•
Technical
•
medium
Explain the concept of the KV cache in autoregressive decoding. How does PagedAttention optimize this process?
#LLM Inference
#Memory Management
#PagedAttention
Machine Learning Engineer
•
Technical
•
hard
Derive the memory requirements for training a 70B parameter model in mixed precision using AdamW and ZeRO-3 optimization.
#Distributed Training
#DeepSpeed
#Memory Profiling
Machine Learning Engineer
•
Technical
•
hard
How does FlashAttention work at a hardware level, and why does it reduce the memory complexity of the attention mechanism from O(N^2) to O(N)?
#Hardware Optimization
#CUDA
#Memory Hierarchy
#FlashAttention
Machine Learning Engineer
•
Technical
•
medium
Explain the differences between Rotary Positional Embeddings (RoPE), ALiBi, and absolute positional embeddings. Why are relative positional embeddings preferred in modern LLMs?
#Transformers
#Positional Encoding
#LLM Architecture
Machine Learning Engineer
•
Technical
•
medium
What is the impact of mixed-precision training (e.g., BF16 vs FP16) on model convergence and memory? Why is BF16 generally preferred for LLMs?
#Numerical Precision
#Hardware
#Training Stability
Machine Learning Engineer
•
Technical
•
hard
Describe mechanistic interpretability. How would you isolate the specific attention head responsible for a specific bias in a Large Language Model?
#Mechanistic Interpretability
#Activation Patching
#Probing
Machine Learning Engineer
•
Technical
•
medium
How do scaling laws apply to model parameters vs. dataset size? Explain the Chinchilla optimal ratio.
#Scaling Laws
#Compute Optimal Training
Machine Learning Engineer
•
Technical
•
hard
What is the Gumbel-Softmax trick, and in what scenarios would you use it in language modeling or reinforcement learning?
#Generative Models
#Reparameterization
#Math
Machine Learning Engineer
•
Technical
•
hard
What are the specific trade-offs between Tensor Parallelism, Pipeline Parallelism, and Fully Sharded Data Parallel (FSDP)?
#Distributed Training
#Parallelism
#GPU Memory
Machine Learning Engineer
•
Technical
•
medium
Explain the KV cache in transformer inference. How do techniques like PagedAttention or Ring Attention optimize it?
#Inference Optimization
#Memory Management
#Attention Mechanisms
Machine Learning Engineer
•
Technical
•
hard
How does Direct Preference Optimization (DPO) mathematically eliminate the need for an explicit reward model compared to PPO?
#RLHF
#DPO
#Optimization
Machine Learning Engineer
•
Technical
•
medium
Explain Constitutional AI and how its pipeline differs from standard Reinforcement Learning from Human Feedback (RLHF).
#Constitutional AI
#RLHF
#AI Safety
Machine Learning Engineer
•
Technical
•
medium
What are the mathematical and practical advantages of using SwiGLU over standard ReLU in Transformer feed-forward networks?
#Activation Functions
#Transformers
#Math
Machine Learning Engineer
•
Technical
•
medium
Why do we use Layer Normalization instead of Batch Normalization in Transformer architectures?
#Normalization
#Transformers
#Math
Machine Learning Engineer
•
Technical
•
medium
How do you handle straggler nodes or hardware failures in synchronous distributed training of large language models?
#Fault Tolerance
#Distributed Training
#Infrastructure
Machine Learning Engineer
•
Technical
•
medium
Explain the difference between Tensor Parallelism (e.g., Megatron-LM) and Pipeline Parallelism. When would you use each?
#Tensor Parallelism
#Pipeline Parallelism
#Model Scaling
Machine Learning Engineer
•
Technical
•
medium
Explain the differences between LoRA, QLoRA, and full fine-tuning. When would you use each at Anthropic?
#PEFT
#LoRA
#Quantization
Machine Learning Engineer
•
Technical
•
hard
What is Direct Preference Optimization (DPO) and how does it compare mathematically and practically to PPO?
#DPO
#RLHF
#Loss Functions
Machine Learning Engineer
•
Technical
•
hard
What causes 'mode collapse' or 'reward hacking' in RLHF, and what regularization techniques prevent the policy model from drifting too far from the reference model?
#Reinforcement Learning
#KL Divergence
#Reward Hacking
Machine Learning Engineer
•
Technical
•
medium
Explain how quantization (e.g., INT8, AWQ, GPTQ) affects model weights and activations. What are the trade-offs in perplexity vs inference speed?
#Quantization
#Inference
#Model Compression
Machine Learning Engineer
•
Technical
•
hard
Discuss the phenomenon of 'grokking' in neural networks. How does weight decay influence it, and what are the implications for LLM training?
#Grokking
#Generalization
#Regularization
Machine Learning Engineer
•
Technical
•
medium
How does Grouped-Query Attention (GQA) bridge the gap between Multi-Head Attention (MHA) and Multi-Query Attention (MQA)?
#Attention Mechanisms
#Inference Efficiency
Machine Learning Engineer
•
Technical
•
hard
Explain the mathematical formulation of RLHF (Reinforcement Learning from Human Feedback). Specifically, how does the PPO objective function work, and what are the common failure modes when fine-tuning a large language model?
#RLHF
#PPO
#Model Alignment
#Optimization
Machine Learning Engineer
•
Technical
•
medium
Describe Anthropic's Constitutional AI. How does it differ from standard RLHF, and how would you implement the critique and revision pipeline programmatically?
#Constitutional AI
#RLAIF
#Prompt Engineering
#Alignment
Machine Learning Engineer
•
Technical
•
hard
Explain the concept of 'sycophancy' in LLMs. How would you design a training objective or dataset to reduce it?
#Sycophancy
#RLHF
#Data Generation
Machine Learning Engineer
•
Technical
•
medium
How does weight decay interact with the Adam optimizer compared to standard SGD? Why was AdamW introduced?
#Optimizers
#AdamW
#Regularization
Machine Learning Engineer
•
Technical
•
medium
How does Rotary Positional Embedding (RoPE) work compared to absolute positional embeddings, and why is it preferred in modern LLMs?
#Embeddings
#Transformers
#RoPE
#Linear Algebra
Machine Learning Engineer
•
Technical
•
hard
Explain the concept of 'Scaling Laws' in language models (e.g., Chinchilla scaling laws). If you have a fixed compute budget, how do you determine the optimal model size and number of training tokens?
#Scaling Laws
#Compute Optimal
#Pre-training
#Resource Allocation
Machine Learning Engineer
•
Technical
•
medium
Explain the vanishing gradient problem and demonstrate mathematically how residual connections (ResNets/Transformers) mitigate it.
#Backpropagation
#Gradients
#Architecture
Machine Learning Engineer
•
Technical
•
medium
What is FlashAttention? Explain how it optimizes memory bandwidth and reduces the time complexity of the attention mechanism.
#FlashAttention
#Memory Bandwidth
#CUDA
#Hardware Optimization
Product Manager
•
Behavioral
•
easy
Tell me about a time you failed to anticipate a user edge case. What happened and how did you resolve it?
#Post-mortems
#User Empathy
#Continuous Improvement
Product Manager
•
Behavioral
•
hard
How do you handle situations where vocal user feedback directly contradicts the company's core safety principles?
#User Feedback
#Principles
#Communication
Product Manager
•
Behavioral
•
medium
Describe a time you successfully influenced a cross-functional team to adopt a new process without having direct authority over them.
#Influence
#Process Improvement
#Team Dynamics
Product Manager
•
Behavioral
•
easy
Why do you want to work at Anthropic specifically, as opposed to other AI labs like OpenAI, Google DeepMind, or Meta?
#Motivation
#Company Knowledge
#AI Industry
Product Manager
•
Behavioral
•
medium
Tell me about a time you had to make a difficult trade-off between shipping a product quickly and ensuring its safety or reliability.
#Safety
#Trade-offs
#Decision Making
Product Manager
•
Behavioral
•
hard
How do you align a team of fundamental AI researchers with strict product engineering timelines and business goals?
#Cross-functional Collaboration
#Research to Product
#Stakeholder Management
Product Manager
•
Behavioral
•
medium
Describe a time you had to make a critical product decision with highly ambiguous or incomplete data.
#Ambiguity
#Data-Informed Decisions
#Risk Taking
Product Manager
•
Behavioral
•
medium
Tell me about a time you strongly disagreed with a technical lead on the architecture or implementation of a feature.
#Conflict Resolution
#Technical Communication
#Influence
Product Manager
•
Behavioral
•
hard
Anthropic values 'steerability' and 'safety'. Tell me about a time you had to trade off rapid user growth for long-term trust and reliability.
#Trade-offs
#Trust & Safety
#Long-term Thinking
Product Manager
•
Behavioral
•
medium
Give an example of a time you had to pivot your product roadmap because of a sudden shift in the competitive landscape.
#Agility
#Competitive Analysis
#Roadmapping
Product Manager
•
Behavioral
•
hard
How do you manage stakeholders with competing priorities, such as the Alignment Research team wanting to delay a launch for safety testing, and the Commercial team needing it for a major client?
#Stakeholder Management
#Negotiation
#Cross-functional Leadership
Product Manager
•
Behavioral
•
medium
Tell me about a time you failed to deliver a product on time. What was the root cause and what did you learn?
#Failure
#Retrospectives
#Project Management
Product Manager
•
Behavioral
•
medium
Tell me about a time you had to pivot your product roadmap based on a sudden shift in the market or a breakthrough in technology.
#Roadmapping
#Agility
#Market Dynamics
Product Manager
•
Behavioral
•
easy
Why do you want to work at Anthropic specifically, rather than OpenAI, Google DeepMind, or Meta?
#Motivation
#Company Knowledge
#Values
Product Manager
•
Behavioral
•
medium
Describe a time you had to pivot a product roadmap due to a sudden shift in the market, such as a competitor releasing a breakthrough model.
#Agile
#Market Dynamics
#Roadmapping
Product Manager
•
Behavioral
•
medium
Describe a time you strongly disagreed with an engineering or research team regarding a technical constraint or model limitation. How did you resolve it?
#Stakeholder Management
#Conflict Resolution
#Cross-functional Collaboration
Product Manager
•
Behavioral
•
medium
Tell me about a time you disagreed with an engineering team or AI researcher about a technical implementation. How did you resolve it?
#Conflict Resolution
#Stakeholder Management
#Communication
Product Manager
•
Behavioral
•
medium
Tell me about a time you had to balance aggressive product growth targets with safety, security, or ethical concerns.
#Ethics
#Decision Making
#Leadership
Product Manager
•
Behavioral
•
hard
Anthropic has limited compute resources. How would you prioritize feature requests for the Claude API between a highly requested developer feature and a critical safety mitigation?
#Prioritization
#Resource Management
#Trade-offs
Product Manager
•
Behavioral
•
medium
A major enterprise customer wants to fine-tune Claude on their proprietary data, but it risks leaking PII. How do you handle this request?
#Data Privacy
#Client Negotiation
#AI Safety
Product Manager
•
Behavioral
•
medium
Tell me about a time you had to delay or cancel a product launch due to safety, security, or ethical concerns.
#Ethics
#Decision Making
#Integrity
Product Manager
•
Coding
•
medium
Write a SQL query to calculate the weekly retention rate of Claude Pro users who have used the 'Artifacts' feature at least once.
#Data Analysis
#Retention
#SQL
Product Manager
•
Coding
•
medium
Write a SQL query to calculate the week-over-week retention rate of developers using the Anthropic API.
#SQL
#Retention
#Cohort Analysis
Product Manager
•
Coding
•
easy
Write a Python script to parse a JSON log file containing user prompts and calculate the average prompt length in characters.
#Python
#Data Parsing
#Scripting
Product Manager
•
Coding
•
medium
Write pseudo-code or a Python script to parse a dataset of 10,000 user prompts and identify the top 5 most common user intents.
#Python
#NLP
#Data Processing
Product Manager
•
Coding
•
medium
Write a SQL query to find the top 5 enterprise customers who have experienced the highest week-over-week percentage increase in API error rates (HTTP 5xx).
#Data Analysis
#SQL
#API Metrics
Product Manager
•
Coding
•
easy
Write a SQL query to find the top 5% of API users by total token usage over the last 30 days.
#Data Analysis
#SQL
#Percentiles
Product Manager
•
System Design
•
hard
How would you build a feature that allows users to seamlessly and automatically switch between different Claude model families (Haiku, Sonnet, Opus) based on the complexity of their prompt?
#Routing
#Model Selection
#Latency
Product Manager
•
System Design
•
medium
Design a product leveraging Claude specifically tailored for legal professionals. What are the core features and risks?
#Domain-Specific AI
#Risk Mitigation
#User Experience
Product Manager
•
System Design
•
hard
Design a system to detect and mitigate prompt injection attacks at scale for our API customers.
#Security
#API Infrastructure
#Adversarial AI
Product Manager
•
System Design
•
hard
A major enterprise customer wants to fine-tune Claude on their proprietary, highly sensitive data. How do you design the product offering to ensure privacy and safety?
#Data Privacy
#Fine-Tuning
#Enterprise Architecture
Product Manager
•
System Design
•
medium
Design the architecture for a RAG (Retrieval-Augmented Generation) system for an enterprise customer wanting to search their internal knowledge base.
#RAG
#Vector Databases
#Architecture
Product Manager
•
System Design
•
medium
How would you design a rate-limiting system for the Anthropic API to handle sudden spikes in traffic while ensuring fairness among different pricing tiers?
#Infrastructure
#API Design
#Scalability
Product Manager
•
System Design
•
medium
Design a feedback loop system to continuously improve Claude's responses based on implicit and explicit user interactions on Claude.ai.
#Data Pipelines
#User Feedback
#Continuous Improvement
Product Manager
•
System Design
•
medium
If you were the PM for Claude's system prompts, how would you design a system to version control and deploy changes to them without disrupting enterprise clients who rely on consistent behavior?
#Version Control
#Deployment
#Enterprise Software
Product Manager
•
System Design
•
hard
How would you design the telemetry and logging architecture for Claude user interactions to improve model safety and evaluations, without violating strict user data privacy requirements?
#Privacy
#Data Logging
#Safety
#Compliance
Product Manager
•
System Design
•
medium
Design a user-facing feature for Claude's web interface that helps users verify the factual accuracy of the model's outputs and mitigates the impact of hallucinations.
#UX/UI
#Hallucinations
#Trust & Safety
Product Manager
•
System Design
•
hard
Design a rate-limiting and quota management system for the Anthropic API that prevents malicious abuse while ensuring enterprise customers experience zero throttling.
#API Design
#Rate Limiting
#Enterprise Requirements
Product Manager
•
System Design
•
medium
How would you design a caching layer for LLM responses to reduce compute costs for frequently asked questions?
#Caching
#Cost Optimization
#Semantic Search
Product Manager
•
System Design
•
hard
Design a scalable A/B testing framework specifically for evaluating different versions of a system prompt for Claude.
#A/B Testing
#Experimentation
#LLM Evaluation
Product Manager
•
System Design
•
hard
Walk me through how you would design a system to detect and block prompt injection attacks in real-time.
#AI Safety
#Security
#Real-time Processing
Product Manager
•
System Design
•
medium
Design a telemetry system to monitor model latency and token generation speed across different geographic regions.
#Observability
#Metrics
#Distributed Systems
Product Manager
•
System Design
•
medium
How would you scale the Claude web interface to handle a 10x spike in traffic during a major new model release?
#Scalability
#Load Balancing
#Queueing
Product Manager
•
System Design
•
hard
Design the backend architecture for a feature that allows users to upload and query 100-page PDF documents using Claude.
#Document Processing
#Vector Databases
#Architecture
Product Manager
•
System Design
•
hard
How would you design a rate-limiting strategy for the Anthropic API that maximizes revenue while preventing platform abuse?
#API Design
#Rate Limiting
#Monetization
Product Manager
•
Technical
•
medium
You notice a 15% drop in API usage from our top-tier developers over the weekend. How do you investigate this?
#Root Cause Analysis
#Data Analytics
#API
Product Manager
•
Technical
•
hard
Should Anthropic build and release a model specifically fine-tuned for code generation, or rely on general-purpose models? Defend your answer.
#Product Strategy
#Model Training
#Market Dynamics
Product Manager
•
Technical
•
medium
How would you prioritize features for the Claude Pro subscription versus the free tier?
#Monetization
#User Segmentation
#Feature Prioritization
Product Manager
•
Technical
•
medium
Explain Constitutional AI and how its principles impact the product development lifecycle at Anthropic.
#Constitutional AI
#Safety
#Communication
Product Manager
•
Technical
•
hard
Imagine we deploy a new version of Claude. Helpfulness scores increase by 8%, but average inference latency increases by 15%. How do you decide whether to roll this out to 100% of users?
#Trade-offs
#Metrics
#A/B Testing
#Latency
Product Manager
•
Technical
•
hard
How would you design an evaluation framework to measure the success of a new coding-specific capability in Claude?
#Model Evals
#Metrics
#Developer Experience
Product Manager
•
Technical
•
hard
A major competitor releases a new LLM that is 50% cheaper and 20% faster than our current flagship model, with comparable reasoning capabilities. How do you adjust our product strategy?
#Competitive Analysis
#Pricing
#Go-to-Market
Product Manager
•
Technical
•
hard
How do you balance context window size, inference cost, and user experience when designing a Retrieval-Augmented Generation (RAG) feature for enterprise clients?
#RAG
#Context Windows
#Cost Optimization
#Enterprise
Product Manager
•
Technical
•
hard
Walk me through the end-to-end go-to-market strategy for launching a new API endpoint that allows enterprise customers to fine-tune Claude on their proprietary data.
#GTM
#Fine-tuning
#Enterprise API
#Launch Strategy
Product Manager
•
Technical
•
hard
We have a new model update that significantly improves performance on coding tasks but slightly degrades performance on creative writing. Do we ship it? Walk me through your decision framework.
#Trade-offs
#Decision Making
#Model Evaluations
Product Manager
•
Technical
•
medium
Design a new feature for Claude specifically aimed at helping software engineers debug legacy enterprise codebases.
#User Experience
#Developer Tools
#Generative AI
Product Manager
•
Technical
•
hard
How would you design an evaluation framework for a new multimodal (vision) feature in Claude before it goes to public beta?
#Multimodal AI
#Evaluations
#Product Launch
Product Manager
•
Technical
•
hard
How would you monetize Claude for enterprise customers without compromising Anthropic's strict data privacy and safety standards?
#Monetization
#Enterprise SaaS
#Data Privacy
Product Manager
•
Technical
•
hard
How do you decide when a new foundational model is 'safe enough' to release to the public?
#Risk Assessment
#Red Teaming
#Launch Strategy
Product Manager
•
Technical
•
hard
Anthropic is considering launching a specialized medical LLM. Walk me through your go-to-market strategy and the risks involved.
#Go-to-Market
#Risk Management
#Healthcare AI
Product Manager
•
Technical
•
medium
Should Anthropic build a first-party plugin ecosystem for Claude or focus on integrating natively with existing enterprise tools like Salesforce and Jira?
#Ecosystem Strategy
#Integrations
#Platform PM
Product Manager
•
Technical
•
medium
Daily active users for Claude.ai dropped by 15% week-over-week. Walk me through your debugging process.
#Analytics
#Root Cause Analysis
#Metrics
Product Manager
•
Technical
•
hard
How do you balance model helpfulness with model harmlessness when designing user-facing features for Claude?
#Constitutional AI
#Trust & Safety
#Trade-offs
Product Manager
•
Technical
•
medium
Design an A/B test to evaluate a new default system prompt for Claude. What are your null and alternative hypotheses, and what metrics determine success?
#A/B Testing
#Statistics
#System Prompts
Product Manager
•
Technical
•
medium
What is the biggest UX challenge in conversational AI today, and how would you solve it within the Claude interface?
#UX/UI
#Conversational AI
#Innovation
Product Manager
•
Technical
•
medium
How do you forecast compute requirements (GPUs/TPUs) for a new feature launch like 'Artifacts'?
#Capacity Planning
#Infrastructure
#Forecasting
Product Manager
•
Technical
•
hard
Design an evaluation framework to decide when a new Claude model (e.g., Claude 3.5 Opus) is ready to be deployed to the public.
#Model Evaluation
#Red Teaming
#Launch Readiness
Product Manager
•
Technical
•
medium
What metrics would you track to evaluate the quality of Claude's long-context summarization capabilities?
#Metrics
#LLM Evaluation
#User Experience
Product Manager
•
Technical
•
medium
How would you prioritize features for the Anthropic API platform given highly constrained ML engineering bandwidth?
#Prioritization
#API Product Management
#Resource Allocation
Product Manager
•
Technical
•
hard
If we introduce a new Constitutional AI principle to reduce bias, how would you measure its success and ensure it doesn't degrade Claude's coding capabilities?
#Model Evaluations
#Constitutional AI
#A/B Testing
Product Manager
•
Technical
•
medium
Evaluate the trade-offs between offering enterprise customers a larger, highly capable model (like Opus) versus a smaller, faster model (like Haiku). How do you guide a customer to the right choice?
#LLM Economics
#Customer Success
#Latency vs Accuracy
Product Manager
•
Technical
•
medium
We are noticing an increase in user reports that Claude is refusing to answer benign prompts (over-refusal). Walk me through how you would investigate and resolve this issue.
#Root Cause Analysis
#AI Safety
#Metrics
Product Manager
•
Technical
•
medium
Evaluate the success of the Claude Pro subscription. What specific metrics would you look at beyond just MRR?
#Product Metrics
#Retention
#Subscription Models
Product Manager
•
Technical
•
medium
A major enterprise customer complains that Claude is hallucinating facts about their internal documents when using our API. How do you triage and resolve this?
#Customer Support
#Hallucinations
#Troubleshooting
Product Manager
•
Technical
•
medium
Explain the concept of Reinforcement Learning from Human Feedback (RLHF) to a non-technical enterprise client.
#Technical Communication
#AI/ML
#Client Facing
Product Manager
•
Technical
•
medium
What are the top 3 north star metrics you would track for the Claude API business, and how would you investigate a sudden 10% drop in daily active API tokens?
#Metrics
#Root Cause Analysis
#API Usage
Product Manager
•
Technical
•
medium
Explain the concept of Constitutional AI to a non-technical enterprise stakeholder.
#Constitutional AI
#Communication
#AI Safety
Product Manager
•
Technical
•
medium
Explain the difference between prompt engineering, RAG, and fine-tuning. When would you recommend each to an enterprise client?
#RAG
#Fine-tuning
#Prompt Engineering
Product Manager
•
Technical
•
medium
An enterprise customer complains that the Claude API is hallucinating facts about their company. How do you investigate and resolve this?
#Hallucinations
#Debugging
#Customer Support
Product Manager
•
Technical
•
hard
From a product management perspective, what are the implications of using RLHF (Reinforcement Learning from Human Feedback) versus RLAIF (AI Feedback)?
#RLHF
#RLAIF
#Scalability
Product Manager
•
Technical
•
hard
How does increasing the context window size (e.g., to 200k tokens) impact latency, compute cost, and the end-user experience?
#Context Windows
#Performance Trade-offs
#LLM Architecture
Product Manager
•
Technical
•
hard
Explain the concept of attention mechanisms in Transformer models as if I were a high school student.
#Technical Communication
#Transformers
#AI/ML
Product Manager
•
Technical
•
medium
Pitch a monetization strategy for Claude in the B2B space that differentiates us from OpenAI's enterprise offerings.
#Monetization
#B2B
#Competitive Analysis
Product Manager
•
Technical
•
medium
What do you believe is the biggest bottleneck in LLM deployment today, and how would you build a product or feature to address it?
#Industry Trends
#Product Vision
#Problem Solving
Product Manager
•
Technical
•
hard
Imagine we are launching a 'Claude for Healthcare' product. What are the regulatory and technical hurdles, and how do you sequence the roadmap?
#Healthcare
#Compliance
#Roadmapping
Software Engineer
•
Behavioral
•
medium
Tell me about a time you discovered a critical bug or security vulnerability right before a major launch. What did you do?
#Crisis Management
#Integrity
#Communication
Software Engineer
•
Behavioral
•
medium
Describe a situation where you strongly disagreed with a technical decision made by your team or manager. How did you handle it?
#Conflict Resolution
#Communication
#Teamwork
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a tradeoff between shipping a feature quickly and ensuring the system's safety or reliability. How did you navigate that decision?
#Tradeoffs
#Safety
#Communication
Software Engineer
•
Behavioral
•
easy
Tell me about a time you had to learn a complex new technology, framework, or domain on the fly to deliver a project. How did you approach the learning process?
#Adaptability
#Learning
#Problem Solving
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to balance shipping a feature quickly versus ensuring its safety, security, or reliability. How did you make the trade-off?
#AI Safety
#Decision Making
#Ethics
Software Engineer
•
Behavioral
•
hard
Describe a time you identified a critical security, privacy, or safety flaw in a system. How did you discover it, and how did you drive the remediation?
#Security
#Proactivity
#Impact
Software Engineer
•
Behavioral
•
hard
Tell me about the most complex debugging experience of your career. What made it difficult, and what did you learn?
#Debugging
#Resilience
#Technical Depth
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to balance shipping a feature quickly with ensuring the system remained safe, secure, or highly reliable.
#Safety
#Trade-offs
#Decision Making
Software Engineer
•
Behavioral
•
medium
How do you handle situations where an ML researcher proposes an architecture or feature that is theoretically sound but practically unscalable or an engineering nightmare?
#Collaboration
#Conflict Resolution
#Cross-functional
Software Engineer
•
Behavioral
•
medium
How do you handle ambiguity in product requirements, especially in a fast-moving and experimental field like generative AI?
#Ambiguity
#Product Sense
#Agile
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to dive deep into a complex, unfamiliar codebase to fix a critical bug. What was your approach?
#Debugging
#Adaptability
#Problem Solving
Software Engineer
•
Behavioral
•
easy
Describe a time you had to dive into a complex codebase in a language or framework you were completely unfamiliar with to fix a critical bug.
#Learning
#Problem Solving
Software Engineer
•
Behavioral
•
easy
Why Anthropic? What specific aspects of our research, products, or mission around Constitutional AI and safety draw you here over other AI labs?
#Motivation
#Company Knowledge
#AI Safety
Software Engineer
•
Behavioral
•
medium
How do you prioritize your engineering tasks when everything seems urgent, and requirements are highly ambiguous?
#Prioritization
#Ambiguity
#Time Management
Software Engineer
•
Behavioral
•
medium
Describe a project where you had to significantly optimize the performance of a system. What was the bottleneck, how did you identify it, and what was the solution?
#Performance
#Profiling
#Impact
Software Engineer
•
Behavioral
•
easy
Why do you want to work at Anthropic specifically, as opposed to other major AI labs like OpenAI or Google DeepMind?
#Company Knowledge
#Motivation
#AI Safety
Software Engineer
•
Behavioral
•
medium
Describe a time you strongly disagreed with a technical direction proposed by a senior engineer or manager. How did you handle the situation and what was the outcome?
#Conflict Resolution
#Communication
#Technical Leadership
Software Engineer
•
Coding
•
hard
Implement a basic Byte Pair Encoding (BPE) tokenizer. Given a string of text and a target vocabulary size, write a function to iteratively merge the most frequent adjacent pairs of characters or subwords.
#Strings
#Hash Maps
#Priority Queue
#LLM Fundamentals
Software Engineer
•
Coding
•
medium
Given a Directed Acyclic Graph (DAG) representing a chain of LLM prompts where some prompts depend on the outputs of others, write an execution engine that runs the prompts in the correct order, maximizing concurrency.
#Graphs
#Topological Sort
#Concurrency
#Asyncio
Software Engineer
•
Coding
•
hard
Given an array of integers representing the execution times of tasks and an integer K representing the number of available workers, write a function to assign tasks to workers to minimize the maximum time spent by any worker.
#Binary Search
#Greedy Algorithms
#Optimization
Software Engineer
•
Coding
•
hard
Write a custom JSON parser that can recover from common malformed outputs generated by LLMs (e.g., missing closing brackets, trailing commas, unescaped quotes).
#Parsing
#String Manipulation
#Heuristics
Software Engineer
•
Coding
•
medium
Implement a thread-safe asynchronous queue from scratch using basic concurrency primitives (mutexes, condition variables).
#Concurrency
#Data Structures
#Synchronization
Software Engineer
•
Coding
•
easy
Write a function to manage a sliding context window for an LLM. Given a list of messages and a maximum token limit, return the optimal subset of messages that fits, ensuring the system prompt is always included.
#Arrays
#Greedy Algorithms
#Logic
Software Engineer
•
Coding
•
medium
Given a string of text and a list of overlapping highlight annotations (start_index, end_index, label), write a function to merge overlapping intervals and return a flattened list of text segments.
#Intervals
#Sorting
#Arrays
Software Engineer
•
Coding
•
medium
Given a set of Constitutional AI rules represented as a directed acyclic graph (where edges represent dependencies between rules), write a function to determine a valid execution order.
#Graphs
#Topological Sort
#DFS/BFS
Software Engineer
•
Coding
•
easy
Write a retry decorator in Python that implements exponential backoff with jitter. It should take parameters for maximum retries, base delay, and exceptions to catch.
#Python
#Decorators
#Networking
#Math
Software Engineer
•
Coding
•
medium
Implement a Trie (Prefix Tree) to support fast autocomplete suggestions. Include a method to insert words with a frequency score, and a method to retrieve the top 3 most frequent completions for a given prefix.
#Trees
#Trie
#Design
#Sorting
Software Engineer
•
Coding
•
medium
Write a function that takes a long string of text and a maximum line length, and returns the text word-wrapped. Words longer than the line length should be broken with a hyphen.
#Strings
#Formatting
#Edge Cases
Software Engineer
•
Coding
•
hard
Implement a text diffing algorithm. Given two strings (an original prompt and an edited prompt), return a list of operations (Insert, Delete, Keep) to transform the original into the edited version.
#Dynamic Programming
#Strings
Software Engineer
•
Coding
•
hard
Implement a basic Key-Value (KV) cache data structure used in transformer attention mechanisms. It needs to support appending new tokens, evicting the oldest tokens when a max length is reached, and fast retrieval.
#Data Structures
#Linked Lists
#Hash Maps
Software Engineer
•
Coding
•
hard
Write a concurrent web scraper that fetches a list of URLs. It must respect robots.txt, enforce a maximum of N concurrent requests per domain, and handle retries with exponential backoff.
#Concurrency
#Web Scraping
#Error Handling
Software Engineer
•
Coding
•
medium
Implement an LRU (Least Recently Used) cache. Once completed, discuss how you would modify it to support an LFU (Least Frequently Used) eviction policy for LLM prompt caching.
#Caching
#Hash Map
#Linked List
Software Engineer
•
Coding
•
hard
Implement a basic version of the scaled dot-product attention mechanism using pure NumPy. Include an optional causal mask.
#Linear Algebra
#NumPy
#Transformers
Software Engineer
•
Coding
•
medium
Implement a text chunking algorithm that takes a large document and splits it into chunks of maximum N tokens, ensuring that chunks only break on sentence boundaries.
#NLP
#String Manipulation
#Edge Cases
Software Engineer
•
Coding
•
medium
Write a function to parse a raw stream of Server-Sent Events (SSE) and yield complete JSON objects. The network can chunk the data at arbitrary byte boundaries.
#String Manipulation
#Networking
#Streaming
Software Engineer
•
Coding
•
medium
Given a massive log file of API requests, write a script to find the top K users who experienced the highest error rates in a specific 5-minute sliding window.
#Sliding Window
#Heaps
#Log Parsing
Software Engineer
•
Coding
•
medium
Implement a Trie-based caching mechanism to store and retrieve LLM prompt prefixes, returning the longest matching cached prefix for a new prompt.
#Trees
#Caching
#String Matching
Software Engineer
•
Coding
•
hard
Write an asynchronous task batcher. It should accept individual requests, wait for either a maximum batch size or a maximum time window, and then process the batch together.
#Asynchronous Programming
#Concurrency
#System Timers
Software Engineer
•
Coding
•
medium
Implement a parser for Server-Sent Events (SSE) that consumes a raw byte stream from an LLM and yields complete JSON objects, handling network interruptions and fragmented chunks.
#I/O Streaming
#State Machines
#String Parsing
Software Engineer
•
Coding
•
hard
Write a simplified Byte Pair Encoding (BPE) tokenizer. Given a corpus of text and a target vocabulary size, implement the training loop to find the most frequent adjacent character pairs and merge them.
#String Manipulation
#Hash Maps
#Heaps
Software Engineer
•
Coding
•
medium
Implement a token bucket rate limiter to throttle incoming API requests based on a user's tier. It should handle concurrent requests safely.
#Concurrency
#Data Structures
#API Design
Software Engineer
•
Coding
•
easy
Given a list of conversation logs with start and end timestamps, write a function to merge overlapping intervals to find the total continuous time a user spent interacting with the model.
#Sorting
#Arrays
#Intervals
Software Engineer
•
Coding
•
medium
Implement an LRU Cache with a Time-To-Live (TTL) feature. If an item is accessed after its TTL has expired, it should be treated as a cache miss and removed.
#Linked Lists
#Hash Maps
#Caching
Software Engineer
•
Coding
•
hard
Design a streaming JSON parser. In our LLM inference API, Claude streams responses token by token. Sometimes the output is a JSON object, but the client receives it in incomplete chunks. Write a function that takes a stream of characters and yields the deepest valid JSON structure possible at any given moment.
#Parsing
#State Machines
#Trees
#Streaming
Software Engineer
•
Coding
•
medium
Write a rate limiter for an API. The rate limiter should support different limits based on the user's tier (e.g., free vs. paid) and should be based on the number of tokens generated, not just the number of requests.
#Concurrency
#Token Bucket
#Object-Oriented Design
Software Engineer
•
Coding
•
medium
Implement an asynchronous task queue in Python using asyncio. The queue should support task priorities, concurrent worker limits, and graceful shutdown.
#Python
#Asyncio
#Concurrency
#Heaps
Software Engineer
•
Coding
•
medium
Write a function to compute the cosine similarity between two dense vectors. Then, optimize it to find the top K most similar vectors from a massive list of vectors (e.g., 1 million) as quickly as possible.
#Math
#Arrays
#Heaps
#Optimization
Software Engineer
•
Coding
•
medium
Implement a token bucket rate limiter for an API endpoint. Extend it to handle distributed rate limiting across multiple servers.
#Concurrency
#API Design
#Distributed Systems
Software Engineer
•
Coding
•
medium
Write a program to parse a massive log file (e.g., 50GB) to find the top 10 most frequent IP addresses. You have limited RAM (e.g., 1GB).
#File I/O
#Hashing
#Heaps
#Memory Management
Software Engineer
•
Coding
•
easy
Implement a sliding window algorithm to manage an LLM's context window. Given an array of text chunks with token counts and a maximum token limit, find the contiguous subarray of chunks that maximizes the token count without exceeding the limit.
#Sliding Window
#Arrays
#Two Pointers
Software Engineer
•
System Design
•
hard
Design a distributed Key-Value store specifically optimized for caching LLM prompt embeddings. It needs to support high read throughput and fast eviction.
#Distributed Systems
#Caching
#Consistent Hashing
#Replication
Software Engineer
•
System Design
•
hard
Design a streaming inference API architecture. How do you route incoming requests to available GPU workers, handle worker failures mid-stream, and stream the generated tokens back to the client?
#Load Balancing
#Streaming
#Fault Tolerance
#GPU Infrastructure
Software Engineer
•
System Design
•
medium
Design a telemetry and logging system for tracking model hallucinations or safety violations in production. The system must handle millions of events per minute without impacting the critical path of the inference API.
#Logging
#Asynchronous Processing
#Big Data
#Observability
Software Engineer
•
System Design
•
hard
Design a distributed caching layer for LLM responses to serve identical queries instantly. How do you handle cache invalidation, semantic similarity, and high read/write throughput?
#Caching
#Vector Databases
#Distributed Systems
Software Engineer
•
System Design
•
hard
Design a telemetry and monitoring system for a cluster of 10,000 GPUs. It needs to detect hardware failures, thermal throttling, and network bottlenecks in real-time.
#Monitoring
#Distributed Systems
#Hardware Infrastructure
Software Engineer
•
System Design
•
medium
Design an A/B testing framework specifically for evaluating new versions of an LLM. How do you route traffic, measure qualitative metrics (like helpfulness), and ensure statistical significance?
#A/B Testing
#Data Engineering
#Analytics
Software Engineer
•
System Design
•
medium
Design an asynchronous batch processing system for offline LLM inference (e.g., processing millions of documents for embeddings).
#Batch Processing
#Message Queues
#Scalability
Software Engineer
•
System Design
•
hard
Design a real-time collaborative prompt engineering tool (similar to Google Docs for prompts) where multiple users can edit, test, and version-control prompts simultaneously.
#Real-time Systems
#Operational Transformation
#WebSockets
Software Engineer
•
System Design
•
medium
Design a rate-limiting service that supports multiple dimensions: per user, per organization, and per IP address, with different limits for each.
#API Design
#Redis
#Scalability
Software Engineer
•
System Design
•
medium
Design the backend architecture for Claude.ai's chat interface. How would you handle conversation history, branching conversations (editing a previous prompt), and streaming responses to the frontend?
#API Design
#WebSockets/SSE
#Database Schema
#State Management
Software Engineer
•
System Design
•
hard
Design a distributed web crawler tailored for gathering LLM training data. How do you handle deduplication at a massive scale, respect robots.txt, and prioritize high-quality domains?
#Distributed Systems
#Message Queues
#Hashing
#Data Pipelines
Software Engineer
•
System Design
•
hard
Design a multi-tenant Retrieval-Augmented Generation (RAG) system for enterprise clients. How do you ensure data isolation, scalable vector search, and low-latency retrieval?
#Vector Databases
#Security
#Multi-tenancy
#Search
Software Engineer
•
System Design
•
hard
Design a system to evaluate LLM outputs for safety and alignment (Constitutional AI pipeline). How would you architect a high-throughput asynchronous pipeline that runs multiple smaller classifier models on Claude's outputs before returning them to the user?
#Microservices
#Stream Processing
#Latency Optimization
#Machine Learning Infrastructure
Software Engineer
•
System Design
•
medium
Design an asynchronous batch processing system for offline LLM generation tasks (e.g., summarizing millions of documents). How do you handle retries, partial failures, and dynamic scaling of GPU workers?
#Batch Processing
#Message Queues
#Fault Tolerance
#GPU Infrastructure
Software Engineer
•
System Design
•
hard
Design a low-latency inference API for a Large Language Model like Claude. How do you handle request batching, streaming responses, and model weight distribution across GPUs?
#Distributed Systems
#Machine Learning Infrastructure
#Latency Optimization
Software Engineer
•
System Design
•
hard
Design a distributed data processing pipeline to ingest, deduplicate, and filter petabytes of web scraping data for LLM pre-training.
#Data Pipelines
#MapReduce
#Storage
Software Engineer
•
System Design
•
medium
Design a system to detect and block prompt injection attacks in real-time across millions of API requests per day.
#Security
#Stream Processing
#Microservices
Software Engineer
•
System Design
•
medium
Design a scalable chat history storage system for a consumer-facing LLM application (like Claude.ai) that allows fast retrieval of recent messages and efficient storage of long contexts.
#Databases
#Caching
#Data Modeling
Software Engineer
•
System Design
•
hard
Design a high-throughput LLM inference service. How would you handle continuous batching, KV cache memory management, and streaming responses back to the client?
#ML Infrastructure
#Distributed Systems
#GPU Memory Management
Software Engineer
•
System Design
•
hard
Design a distributed data pipeline to process petabytes of raw web text for LLM pre-training. It needs to filter out PII, deduplicate documents, and tokenize the text.
#Big Data
#Data Pipelines
#MapReduce
Software Engineer
•
System Design
•
hard
Design a system to monitor, detect, and block prompt injection attacks in real-time across millions of API requests per minute.
#Security
#Stream Processing
#Low Latency
Software Engineer
•
System Design
•
medium
Design a scalable model evaluation framework. Researchers need to run thousands of benchmark tests (MMLU, HumanEval) against new model checkpoints daily.
#Task Queues
#Scalability
#CI/CD
Software Engineer
•
System Design
•
hard
Design a global API rate limiting system for Anthropic's enterprise customers. It must be highly available, have minimal latency impact, and strictly enforce limits across multiple geographic regions.
#Distributed Systems
#Redis
#Rate Limiting
#Consistency
Software Engineer
•
System Design
•
medium
Design a system for securely storing and querying user conversation history with Claude. The system must ensure strict privacy, support fast retrieval for context windows, and comply with data deletion requests.
#Databases
#Privacy
#Security
Software Engineer
•
Technical
•
medium
How would you debug a severe memory leak in a Python application that processes large volumes of text data for model training?
#Python
#Memory Management
#Profiling
#Garbage Collection
Software Engineer
•
Technical
•
medium
How would you implement distributed locking for a shared resource in an AWS environment to ensure only one worker processes a specific task at a time?
#AWS
#Concurrency
#Locks
Software Engineer
•
Technical
•
hard
How would you optimize PyTorch dataloaders for training a model on a massive, multi-terabyte text dataset stored in AWS S3?
#PyTorch
#Data Pipelines
#Cloud Storage
#Performance Optimization
Software Engineer
•
Technical
•
medium
Explain the trade-offs between using gRPC versus REST for internal microservices communication in a high-throughput environment.
#Networking
#Protocols
#Microservices
Software Engineer
•
Technical
•
medium
Explain how you would optimize a Python microservice that has become CPU-bound due to heavy text processing and regex matching.
#Python
#GIL
#Profiling
Software Engineer
•
Technical
•
hard
Explain how Key-Value (KV) caching works during transformer inference. Why is it necessary, and what are the memory implications for long context windows?
#Transformers
#Inference
#Memory Management
#LLM Architecture
Software Engineer
•
Technical
•
medium
Design the database schema for a chat application like Claude. It must support users, chat sessions, individual messages, and the ability to 'edit and retry' a message, which creates a new branch of the conversation.
#SQL
#Database Schema
#Trees
#Data Modeling
Software Engineer
•
Technical
•
medium
How do you handle backpressure in a streaming data pipeline? Imagine a scenario where our inference engines are producing tokens faster than the client's network connection can receive them.
#Networking
#Streaming
#TCP/IP
#Concurrency
Software Engineer
•
Technical
•
medium
Discuss the challenges of managing state in a WebSocket-based streaming application. How do you handle load balancing, connection drops, and state recovery?
#WebSockets
#Networking
#State Management
Software Engineer
•
Technical
•
hard
Here is an asynchronous Python script used for concurrent API scraping that is randomly deadlocking. Walk me through how you would debug and fix it.
#Python
#Asyncio
#Debugging
Software Engineer
•
Technical
•
hard
How does memory fragmentation affect long-running processes in languages like Rust or C++, and what strategies would you use to mitigate it in a high-throughput API server?
#Memory Management
#Rust
#C++
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