OpenAI
Leading AI research laboratory developing state-of-the-art foundation models like GPT-4.
5 Rounds
~21 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 identified a major bottleneck in a system and took the initiative to fix it without being asked.
#Initiative
#Performance Optimization
#Ownership
Backend Engineer
•
Behavioral
•
medium
OpenAI moves at a very fast pace. Tell me about a time you had to learn a completely new technology to deliver a project on tight deadlines.
#Learning Agility
#Time Management
#Adaptability
Backend Engineer
•
Behavioral
•
hard
What is the most complex distributed systems failure you have ever encountered, and what did you learn from it?
#Post-mortems
#Distributed Systems
#Resilience
Backend Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a senior engineer or manager about a system architecture. How did you resolve it?
#Conflict Resolution
#Communication
#Influence
Backend Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a technical tradeoff between shipping quickly and building a perfectly scalable system.
#Trade-offs
#Productivity
#Decision Making
Backend Engineer
•
Behavioral
•
medium
How do you handle working on a project where the requirements are highly ambiguous and constantly changing?
#Ambiguity
#Adaptability
#Agile
Backend Engineer
•
Behavioral
•
medium
Describe a situation where you had to debug a complex production incident under high pressure. What was your process?
#Incident Response
#Debugging
#Communication
Backend Engineer
•
Coding
•
medium
Write a program to resolve dependencies for a set of AI agents. Given a list of agents and their dependencies, output a valid execution order.
#Graphs
#Topological Sort
#BFS/DFS
Backend Engineer
•
Coding
•
hard
Implement a text justification algorithm. Given an array of words and a maximum width, format the text such that each line has exactly the maximum width.
#String Manipulation
#Greedy Algorithms
Backend Engineer
•
Coding
•
medium
Write a function to merge K sorted streams of tokens into a single sorted stream. Assume the streams are coming from different backend model replicas.
#Heaps
#Streaming Data
#Pointers
Backend Engineer
•
Coding
•
medium
Implement a token bucket rate limiter that can handle both requests-per-minute and tokens-per-minute limits simultaneously.
#Concurrency
#Data Structures
#Rate Limiting
Backend Engineer
•
Coding
•
medium
Implement a Trie data structure optimized for fast prefix matching to detect blocked keywords in a streaming prompt.
#Trees
#Trie
#String Matching
Backend Engineer
•
Coding
•
hard
Given a stream of nested JSON chunks (which may be fragmented), write a parser that yields valid JSON objects as soon as they are fully formed.
#String Manipulation
#Parsing
#Stacks
Backend Engineer
•
Coding
•
medium
Implement a thread-safe LRU Cache with a Time-To-Live (TTL) for each entry. This would be used to cache recent prompt embeddings.
#Hash Maps
#Linked Lists
#Concurrency
Backend Engineer
•
Coding
•
easy
Given an array of API request start and end times, calculate the maximum number of concurrent requests the server handled.
#Arrays
#Sorting
#Sweep Line
Backend Engineer
•
Coding
•
hard
Implement a distributed task queue executor. You have a central queue and multiple worker nodes. Ensure tasks are executed exactly once.
#Distributed Systems
#Concurrency
#State Machines
Backend Engineer
•
Coding
•
hard
Serialize and deserialize an N-ary tree. This is used to represent branched conversation threads where users edit previous prompts.
#Trees
#Serialization
#DFS/BFS
Backend Engineer
•
Coding
•
medium
Find the longest substring with at most K distinct characters. (Used to optimize context window parsing).
#Sliding Window
#Hash Maps
#Strings
Backend Engineer
•
System Design
•
hard
Design the OpenAI API rate limiting system. It needs to enforce limits on requests per minute (RPM) and tokens per minute (TPM) across millions of users globally with minimal latency.
#Distributed Systems
#Redis
#Latency Optimization
Backend Engineer
•
System Design
•
hard
Design an ingestion pipeline for training data that continuously processes petabytes of text from the web.
#Data Engineering
#Kafka
#MapReduce
#Storage
Backend Engineer
•
System Design
•
hard
Design a system for streaming LLM responses to millions of concurrent users. How do you handle connection drops and ensure tokens are delivered in order?
#Server-Sent Events (SSE)
#WebSockets
#Load Balancing
#Connection Management
Backend Engineer
•
System Design
•
hard
Design a system to detect and block malicious prompts (jailbreaks) in real-time before they reach the LLM.
#Security
#Stream Processing
#Machine Learning Infrastructure
Backend Engineer
•
System Design
•
hard
Design a vector database for storing and querying billions of embeddings generated by our models.
#Vector Search
#ANN Algorithms
#Sharding
#Databases
Backend Engineer
•
System Design
•
medium
Design ChatGPT's conversation history storage system. It must support fast retrieval of recent chats, full-text search, and handle massive write volume.
#Databases
#Sharding
#Search Engines
Backend Engineer
•
System Design
•
medium
Design a real-time monitoring and alerting system for model inference latency across multiple geographic regions.
#Observability
#Time-Series Databases
#Data Aggregation
Backend Engineer
•
System Design
•
hard
Design a webhook delivery system for asynchronous API requests (e.g., batch processing of millions of prompts).
#Message Queues
#Retry Mechanisms
#Idempotency
#Rate Limiting
Backend Engineer
•
System Design
•
hard
Design a GPU resource scheduler for batch processing inference jobs. Some jobs have higher priority, and GPUs have varying memory capacities.
#Resource Allocation
#Scheduling Algorithms
#Distributed Systems
Backend Engineer
•
System Design
•
medium
Design a scalable distributed cache for LLM prompt/response pairs to save compute on identical queries.
#Caching
#Hashing
#Consistency
Backend Engineer
•
Technical
•
medium
Explain how Server-Sent Events (SSE) work under the hood. What are the load balancing challenges associated with SSE?
#HTTP
#Load Balancing
#TCP/IP
Backend Engineer
•
Technical
•
medium
How do you handle database migrations in a high-availability system with zero downtime?
#Database Migrations
#High Availability
#Deployment
Backend Engineer
•
Technical
•
hard
Explain the Raft consensus algorithm. How does it handle network partitions?
#Consensus
#Raft
#Fault Tolerance
Backend Engineer
•
Technical
•
medium
Describe how you would implement distributed tracing across microservices handling LLM requests to identify latency spikes.
#Distributed Tracing
#Microservices
#OpenTelemetry
Backend Engineer
•
Technical
•
easy
What are the trade-offs between gRPC and REST for internal service-to-service communication in a high-throughput environment?
#gRPC
#REST
#Microservices
Backend Engineer
•
Technical
•
hard
How do you manage memory leaks in a long-running Python asyncio application?
#Memory Management
#Asyncio
#Garbage Collection
Backend Engineer
•
Technical
•
medium
How would you optimize a Python backend service that is CPU-bound due to heavy JSON serialization/deserialization?
#Python
#Profiling
#Serialization
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time a critical deployment failed during a major product launch. How did you handle the situation and the stakeholders?
#Crisis Management
#Communication
#Resilience
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you caused a significant production outage. What happened, how did you fix it, and what did you learn?
#Incident Management
#Accountability
#Post-mortems
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you had to push back on a feature request from a researcher or senior engineer because it was architecturally unsound.
#Conflict Resolution
#Stakeholder Management
Cloud Engineer
•
Behavioral
•
easy
Describe a time you had to learn a deeply technical and complex concept very quickly to solve a critical issue.
#Adaptability
#Learning
#Problem Solving
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you optimized cloud infrastructure costs significantly without degrading system performance.
#FinOps
#Optimization
#Impact
Cloud Engineer
•
Behavioral
•
medium
OpenAI moves at an incredibly fast pace, and priorities can shift overnight. Give an example of how you managed a sudden pivot in a major infrastructure project you were leading.
#Agility
#Project Management
#Communication
Cloud Engineer
•
Behavioral
•
medium
Describe a time you caused a major production outage. How did you handle the immediate mitigation, and what systemic changes did you implement during the post-mortem?
#Post-mortem
#Accountability
#SRE Practices
Cloud Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a significant infrastructure architecture decision with incomplete information under extreme time pressure.
#Decision Making
#Ambiguity
#Pressure
Cloud Engineer
•
Behavioral
•
medium
How do you prioritize addressing engineering debt versus shipping new infrastructure features required by the research teams?
#Prioritization
#Engineering Excellence
#Trade-offs
Cloud Engineer
•
Coding
•
medium
Write a Python script that interacts with the Kubernetes API to find all pods stuck in a 'CrashLoopBackOff' state across all namespaces, logs their last termination reason, and restarts their respective deployments.
#Python
#Kubernetes API
#Scripting
Cloud Engineer
•
Coding
•
hard
Write a function to find the shortest path in a network of microservices to identify the root cause of a cascading failure, given a graph of service dependencies and their current error rates.
#Graphs
#Dijkstra
#BFS
Cloud Engineer
•
Coding
•
hard
Implement a token bucket rate limiter in Python or Go. Explain how you would adapt this to work across a distributed cluster of API gateways.
#Rate Limiting
#Distributed Systems
#Redis
Cloud Engineer
•
Coding
•
medium
Implement a task scheduler that takes a list of tasks with dependencies and executes them in the correct order. If a cycle is detected, throw an error.
#Graphs
#Topological Sort
#DFS/BFS
Cloud Engineer
•
Coding
•
easy
Write a script to validate that a given JSON configuration file for cloud infrastructure strictly adheres to a predefined schema, handling nested objects and arrays.
#JSON
#Validation
#Recursion
Cloud Engineer
•
Coding
•
medium
Write a Go program to concurrently fetch health check endpoints of 10,000 internal services. It should timeout after 5 seconds and return a list of failed services.
#Go
#Goroutines
#Channels
#Context
Cloud Engineer
•
Coding
•
medium
Given a list of IP CIDR blocks, write a function to merge all overlapping blocks and return the minimized list of CIDRs.
#Intervals
#Networking
#Python/Go
Cloud Engineer
•
Coding
•
medium
Write a Go program that concurrently pings a list of 10,000 IP addresses (representing our worker nodes) and returns the IPs that are unreachable. Ensure your solution is highly concurrent but does not exceed OS file descriptor limits.
#Go
#Goroutines
#Channels
#Networking
Cloud Engineer
•
Coding
•
medium
Write a script that automatically cordons and drains Kubernetes nodes if a specific Prometheus alert (e.g., hardware failure) fires for more than 5 minutes.
#Kubernetes API
#Python/Go
#Prometheus
Cloud Engineer
•
Coding
•
easy
Implement a basic load balancer algorithm in code that routes requests to a pool of backend servers using Weighted Round Robin.
#Load Balancing
#Data Structures
#Math
Cloud Engineer
•
Coding
•
medium
Write a Python script to parse a massive stream of distributed logs, identify spikes in specific HTTP 5xx errors, and output the top 3 offending IP addresses.
#Python
#Log Parsing
#Data Structures
#Streaming
Cloud Engineer
•
System Design
•
hard
Explain how you would design the infrastructure to serve a large language model like GPT-4, ensuring high availability and low latency for global users.
#GPU Orchestration
#Load Balancing
#High Availability
#Inference
Cloud Engineer
•
System Design
•
hard
Design a multi-region active-active deployment architecture for the OpenAI API to ensure 99.99% uptime.
#High Availability
#Global Routing
#Database Replication
Cloud Engineer
•
System Design
•
hard
Design a system to securely stream massive training datasets (petabytes of data) from cloud storage to thousands of GPU nodes in real-time.
#Storage
#Throughput
#Distributed Systems
Cloud Engineer
•
System Design
•
medium
Design a scalable CI/CD pipeline for a massive monorepo containing both infrastructure code and machine learning models.
#CI/CD
#Monorepo
#Bazel
#Automation
Cloud Engineer
•
System Design
•
hard
Design a distributed caching layer for LLM embeddings that allows fast nearest-neighbor lookups across billions of vectors.
#Vector Databases
#Caching
#Distributed Systems
Cloud Engineer
•
System Design
•
hard
Design a telemetry and observability system capable of ingesting and querying metrics from 100,000+ GPUs in real-time.
#Observability
#Prometheus
#Time-Series Databases
#Scaling
Cloud Engineer
•
System Design
•
hard
Design a rate-limiting service for the OpenAI API that can handle sudden, massive viral spikes in traffic across multiple global regions.
#Distributed Systems
#API Gateway
#Redis
#Concurrency
Cloud Engineer
•
System Design
•
hard
Design a system to provision, manage, and monitor a cluster of 10,000 GPUs on Azure for a massive LLM training run. How do you handle node failures gracefully without restarting the entire training job?
#Azure
#Kubernetes
#GPU Orchestration
#Fault Tolerance
Cloud Engineer
•
System Design
•
hard
Design an auto-scaling architecture for the ChatGPT inference API that experiences sudden, massive spikes in traffic. How do you scale stateful workloads like KV-cache across multiple regions?
#Auto-scaling
#Load Balancing
#Distributed Systems
#Inference
Cloud Engineer
•
System Design
•
hard
Design a CI/CD pipeline for deploying updates to a mission-critical Kubernetes cluster that serves model inference, ensuring zero downtime and the ability to roll back instantly if error rates spike.
#GitOps
#ArgoCD
#Canary Deployments
#Observability
Cloud Engineer
•
Technical
•
hard
How does packet flow work between two pods on different nodes in a Kubernetes cluster? Walk me through the exact networking path.
#Kubernetes
#CNI
#Linux Networking
#iptables/eBPF
Cloud Engineer
•
Technical
•
medium
How would you implement autoscaling for a Kubernetes cluster based on a custom metric, such as the length of a GPU job queue?
#Kubernetes
#Autoscaling
#Prometheus
Cloud Engineer
•
Technical
•
hard
Model checkpointing generates terabytes of data in seconds. How would you design the storage layer in Azure to handle this massive write burst throughput without bottlenecking the GPU training process?
#Azure Blob Storage
#Lustre
#High Performance Computing
#IOPS
Cloud Engineer
•
Technical
•
medium
We use Azure heavily. Explain the difference between Azure Virtual Network Peering and ExpressRoute, and when you would use each for a hybrid cloud training cluster.
#Azure
#Networking
#Hybrid Cloud
Cloud Engineer
•
Technical
•
medium
How do you manage Terraform state in a large organization where multiple engineers and CI/CD pipelines are applying changes simultaneously?
#Terraform
#CI/CD
#State Management
Cloud Engineer
•
Technical
•
hard
A Kubernetes node is showing high GPU memory utilization but 0% GPU compute utilization. How do you troubleshoot this?
#GPUs
#Kubernetes
#Nvidia SMI
#Linux
Cloud Engineer
•
Technical
•
hard
Explain the Raft consensus algorithm and how etcd uses it. What are the bottlenecks when scaling etcd to thousands of Kubernetes nodes?
#etcd
#Raft
#Kubernetes Internals
Cloud Engineer
•
Technical
•
hard
How would you implement zero-downtime node upgrades in a stateful Kubernetes cluster running distributed ML training jobs?
#Kubernetes
#StatefulSets
#Operations
Cloud Engineer
•
Technical
•
hard
What is RDMA (Remote Direct Memory Access) and why is it critical for distributed GPU training clusters?
#RDMA
#InfiniBand
#GPUs
#Performance
Cloud Engineer
•
Technical
•
medium
Explain what an OOMKilled event is in Kubernetes. How do you determine if it was caused by the container exceeding its limit or the node running out of memory?
#Kubernetes
#Linux
#Memory Management
Cloud Engineer
•
Technical
•
medium
How do you handle secret management and rotation across multiple Kubernetes clusters in different cloud regions?
#Security
#HashiCorp Vault
#Kubernetes
Cloud Engineer
•
Technical
•
hard
You are tasked with writing a Kubernetes Custom Resource Definition (CRD) and Operator to manage the lifecycle of a proprietary ML training job. Walk me through the architecture.
#Kubernetes
#Operators
#Go
Cloud Engineer
•
Technical
•
hard
Troubleshoot a scenario where DNS resolution latency inside a large Kubernetes cluster is sporadically spiking to over 5 seconds.
#DNS
#Kubernetes
#CoreDNS
#Linux
Cloud Engineer
•
Technical
•
medium
How would you design the Azure RBAC and Kubernetes RBAC policies to ensure that researchers have full access to their specific training namespaces but cannot access, view, or modify production inference workloads?
#IAM
#Kubernetes RBAC
#Azure AD
#Least Privilege
Cloud Engineer
•
Technical
•
medium
How do you troubleshoot a scenario where pods in a Kubernetes cluster can communicate with each other perfectly, but intermittently drop connections when reaching out to an external Azure managed database?
#Kubernetes
#SNAT
#DNS
#Troubleshooting
Cloud Engineer
•
Technical
•
hard
Explain how you would secure a multi-tenant Kubernetes cluster where different research teams are running arbitrary code.
#Kubernetes
#Security
#Isolation
Cloud Engineer
•
Technical
•
hard
You notice a high rate of packet drops on a Linux node running heavy GPU inference workloads. Walk me through the tools and steps you would use to diagnose if the bottleneck is at the NIC, the kernel network stack, or the application.
#Linux
#Networking
#Performance Tuning
#eBPF
Cloud Engineer
•
Technical
•
medium
What are the primary bottlenecks when pulling massive Docker images (e.g., 20GB+ Python ML environments) across thousands of nodes simultaneously, and how do you mitigate them?
#Docker
#Containerd
#Networking
#P2P
Cloud Engineer
•
Technical
•
medium
We use Terraform heavily to manage our Azure infrastructure. How would you structure the Terraform state and modules to allow dozens of infrastructure and research teams to deploy concurrently without locking each other out or causing state corruption?
#Terraform
#Azure
#CI/CD
#State Management
Cloud Engineer
•
Technical
•
hard
Explain how you would configure Azure ExpressRoute and VNet peering to ensure secure, ultra-low-latency communication between our training clusters and our massive blob storage accounts.
#Azure Networking
#ExpressRoute
#VNet
#Security
Data Engineer
•
Behavioral
•
easy
Describe a project where you had to learn a completely new technology or framework on the fly to solve a critical business problem.
#Adaptability
#Continuous Learning
#Problem Solving
Data Engineer
•
Behavioral
•
hard
At OpenAI, safety and alignment are critical. How would you handle a situation where you discovered a flaw in a data pipeline that might have introduced biased or unsafe data into a training run?
#Ethics
#Safety
#Integrity
#Incident Response
Data Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a researcher or data scientist about how data should be processed or modeled. How did you resolve it?
#Collaboration
#Conflict Resolution
#Communication
Data Engineer
•
Behavioral
•
medium
OpenAI moves incredibly fast. Tell me about a time you had to make a technical trade-off between shipping quickly and building a perfectly scalable system.
#Trade-offs
#Agile
#Decision Making
Data Engineer
•
Behavioral
•
medium
Describe a time you had to debug a silent data corruption issue. How did you detect it and fix it?
#Debugging
#Data Integrity
#Problem Solving
Data Engineer
•
Behavioral
•
medium
Tell me about a time you had to optimize a data pipeline that was failing or severely bottlenecked under scale. What was the root cause and how did you fix it?
#Performance Tuning
#Problem Solving
#Impact
Data Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a senior engineer or stakeholder about a technical design or architecture. How did you approach the disagreement and what was the outcome?
#Conflict Resolution
#Communication
#Technical Leadership
Data Engineer
•
Behavioral
•
medium
Describe a situation where you had to make a difficult trade-off between data quality and processing speed/delivery time. How did you make your decision?
#Trade-offs
#Data Quality
#Prioritization
Data Engineer
•
Behavioral
•
medium
Describe a time you discovered a critical bug or data corruption issue in your pipeline after it was already in production. How did you handle the incident?
#Incident Management
#Accountability
#Post-mortems
Data Engineer
•
Behavioral
•
medium
Tell me about the most complex data pipeline you've ever built. What made it complex, and what would you do differently today?
#Architecture
#Retrospective
#Experience
Data Engineer
•
Behavioral
•
hard
What is the most complex distributed systems problem you have ever debugged? Walk me through your troubleshooting process from alert to resolution.
#Debugging
#Distributed Systems
#Deep Dive
Data Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a technical tradeoff between data quality and pipeline speed. How did you decide, and what was the outcome?
#Trade-offs
#Decision Making
#Data Quality
Data Engineer
•
Behavioral
•
medium
Tell me about a time you identified a major bottleneck or inefficiency in a data system that no one else noticed. How did you go about fixing it and getting buy-in from the team?
#Ownership
#Proactivity
#Impact
Data Engineer
•
Behavioral
•
medium
Tell me about a time you proactively identified a bottleneck or technical debt in your team's infrastructure and took the initiative to fix it without being asked.
#Initiative
#Technical Debt
#Ownership
Data Engineer
•
Behavioral
•
medium
OpenAI moves very fast and requirements can change rapidly. Tell me about a time you had to deliver a critical project with ambiguous requirements and a tight deadline.
#Ambiguity
#Agility
#Execution
Data Engineer
•
Behavioral
•
medium
OpenAI moves very fast. Describe a situation where you had to build a data pipeline with constantly changing requirements and incomplete upstream data schemas. How did you ensure reliability?
#Ambiguity
#Adaptability
#Reliability
Data Engineer
•
Behavioral
•
easy
Why do you want to join OpenAI specifically, and how do you see the role of a Data Engineer evolving as AI models become more capable of writing code and analyzing data?
#Motivation
#Industry Trends
#AGI
Data Engineer
•
Coding
•
medium
Given a list of text spans representing PII (Personally Identifiable Information) redactions with start and end indices, write a function to merge overlapping intervals efficiently.
#Arrays
#Sorting
#Intervals
Data Engineer
•
Coding
•
medium
Implement a custom MapReduce-like framework in Python using multiprocessing to count token frequencies across multiple large text files.
#Multiprocessing
#Concurrency
#MapReduce
Data Engineer
•
Coding
•
hard
Find the top K most frequent tokens in a continuous, infinite stream of text data.
#Streaming Algorithms
#Heaps
#Count-Min Sketch
Data Engineer
•
Coding
•
medium
Implement a Trie data structure to efficiently scan and redact a dynamic list of blocked phrases from training data strings.
#Trees
#String Matching
#Trie
Data Engineer
•
Coding
•
medium
Write an asynchronous Python script using asyncio and aiohttp to download millions of images from a list of URLs, ensuring a maximum of 100 concurrent requests and implementing exponential backoff for 429 errors.
#Asyncio
#Concurrency
#Error Handling
Data Engineer
•
Coding
•
medium
Write a SQL query to calculate the 7-day rolling average of API requests per user, ensuring days with zero requests are factored into the average.
#Window Functions
#CTEs
#Date Generation
Data Engineer
•
Coding
•
hard
Given a table of user prompts, write a SQL query to find users who have submitted prompts in at least 3 different languages within any rolling 24-hour window.
#Self Joins
#Window Functions
#Time-Series
Data Engineer
•
Coding
•
hard
Write a SQL query to identify ChatGPT session boundaries. A new session starts if there is more than 30 minutes of inactivity between prompts from the same user.
#Gaps and Islands
#Window Functions
#LAG/LEAD
Data Engineer
•
Coding
•
medium
Given a table of model training runs (run_id, model_size, gpu_count, tokens_processed, duration_seconds), write a query to find the run with the highest throughput (tokens per second per GPU) for each model size.
#Ranking
#Window Functions
#Math
Data Engineer
•
Coding
•
medium
Write a SQL query to find the median token count per prompt for each day in the last month.
#Percentiles
#Aggregation
#Date Functions
Data Engineer
•
Coding
•
medium
Write a Python function to parse a massive JSONL file containing web crawl data, filter out documents with a high proportion of non-alphanumeric characters (spam/code), and yield batches of clean text. Assume the file is significantly larger than available RAM.
#Python
#Generators
#Memory Management
#Text Processing
Data Engineer
•
Coding
•
medium
Given a table of API requests (request_id, user_id, model_name, tokens_used, timestamp), write a SQL query to find the top 3 users by token usage for each model over the last 30 days, but only include users who have used at least two different models.
#Window Functions
#CTEs
#Aggregations
Data Engineer
•
Coding
•
hard
Implement a rate limiter for our API. Given a stream of requests, allow a maximum of N requests per minute per user. If a user exceeds this, drop the requests. Optimize for high concurrency and minimal latency.
#Rate Limiting
#Concurrency
#Data Structures
#Redis
Data Engineer
•
Coding
•
medium
Given a list of conversational turns (user prompt, assistant response) with timestamps and session IDs, write a function to reconstruct the conversation threads. Note that some turns might arrive out of order or have missing timestamps.
#Data Structures
#Sorting
#Edge Cases
Data Engineer
•
Coding
•
hard
Design the database schema and write the SQL to track RLHF (Reinforcement Learning from Human Feedback) tasks. We have prompts, multiple model completions, and human rankings. How do you query for the inter-annotator agreement rate?
#Schema Design
#Complex Queries
#RLHF
Data Engineer
•
Coding
•
easy
Write a function to merge overlapping time intervals. We use this to calculate the total active compute time for GPU clusters given a log of job start and end times.
#Intervals
#Sorting
#Python
Data Engineer
•
Coding
•
medium
Write a script to sample exactly K random lines from a massive text file in a single pass.
#Probability
#Reservoir Sampling
#Big Data
Data Engineer
•
Coding
•
medium
Implement an LRU cache with a TTL (Time To Live) for caching database queries.
#Data Structures
#Hash Maps
#Linked Lists
#Caching
Data Engineer
•
Coding
•
medium
Given a list of data pipeline tasks with dependencies, write a function to return a valid execution order.
#Graphs
#Topological Sort
#DAGs
Data Engineer
•
Coding
•
hard
Write a distributed map-reduce job from scratch in Python using multiprocessing to count token frequencies across multiple files.
#Python
#Multiprocessing
#MapReduce
#Concurrency
Data Engineer
•
Coding
•
medium
Implement a function to merge overlapping text intervals (e.g., highlighting spans in a document).
#Sorting
#Arrays
#Intervals
Data Engineer
•
Coding
•
medium
Given a stream of API requests, implement a sliding window rate limiter.
#Data Structures
#Concurrency
#Queues
Data Engineer
•
Coding
•
medium
Write a Python generator to efficiently parse a 500GB JSONL file containing conversation logs without loading the whole file into memory.
#Python
#Memory Management
#Generators
#File I/O
Data Engineer
•
Coding
•
medium
Write a Python generator function to parse a multi-terabyte JSONL file of Common Crawl data, extract the 'text' field, and yield chunks of exactly 10,000 tokens using a provided tokenizer function.
#Generators
#Memory Management
#File I/O
Data Engineer
•
Coding
•
medium
Implement a sliding window rate limiter for the OpenAI API that can handle high concurrency.
#Data Structures
#Concurrency
#Queues
Data Engineer
•
Coding
•
hard
Implement a MinHash and Locality-Sensitive Hashing (LSH) algorithm to find near-duplicate documents in a massive corpus of web text.
#Hashing
#Probability
#Text Processing
#Big Data
Data Engineer
•
System Design
•
hard
Design a data pipeline to ingest, deduplicate, and tokenize 10 petabytes of web text data for LLM pre-training. How do you handle exact and fuzzy deduplication at this massive scale?
#Distributed Systems
#Data Pipelines
#MinHash/LSH
#Spark/Ray
Data Engineer
•
System Design
•
hard
Design a data ingestion pipeline to process petabytes of web crawl data (e.g., CommonCrawl) for LLM pre-training.
#Distributed Systems
#Data Ingestion
#Scalability
#Storage
Data Engineer
•
System Design
•
hard
Design a near real-time telemetry system to track API token usage and latency across millions of ChatGPT users.
#Streaming
#Kafka
#Real-time Analytics
#Metrics
Data Engineer
•
System Design
•
hard
Design a distributed deduplication system to remove exact and near-duplicate documents from a 10TB text dataset.
#Algorithms
#Big Data
#MinHash
#LSH
Data Engineer
•
System Design
•
medium
Design a pipeline to continuously update a vector database with new embeddings generated from daily news articles.
#Vector Databases
#Embeddings
#ETL
#Orchestration
Data Engineer
•
System Design
•
hard
How would you design a system to detect and scrub PII (Personally Identifiable Information) from training datasets at scale?
#Data Privacy
#NLP
#Distributed Processing
#Security
Data Engineer
•
System Design
•
medium
Explain how you would model the data warehouse schema for tracking prompt and completion tokens across different API endpoints.
#Data Modeling
#Star Schema
#Fact/Dimension Tables
Data Engineer
•
System Design
•
hard
Design a data pipeline to ingest, filter for PII, deduplicate, and tokenize 10PB of Common Crawl data for training a next-generation LLM.
#Big Data
#Distributed Systems
#Data Pipelines
#Spark/Ray
Data Engineer
•
System Design
•
medium
Design a real-time analytics and monitoring system for the OpenAI API to track latency, error rates, and token usage globally.
#Stream Processing
#Kafka
#Time-Series DB
#Monitoring
Data Engineer
•
System Design
•
hard
How would you design a highly available, low-latency system to track and enforce token rate limits for OpenAI API users across multiple global regions?
#Distributed Caching
#Redis
#Consistency
#Rate Limiting
Data Engineer
•
System Design
•
hard
Design a pipeline to continuously ingest newly published news articles, generate embeddings using an OpenAI model, and update a vector database for a real-time RAG application.
#Vector Databases
#Embeddings
#Event-Driven Architecture
#RAG
Data Engineer
•
System Design
•
medium
Architect a system to collect, anonymize, and store telemetry and conversation data from ChatGPT clients for model fine-tuning, ensuring strict privacy compliance.
#Data Privacy
#Batch Processing
#Data Warehousing
#Security
Data Engineer
•
System Design
•
hard
Design an automated evaluation pipeline that runs nightly benchmarks (e.g., MMLU, HumanEval) on the latest model checkpoints and alerts researchers to regressions.
#Orchestration
#CI/CD for ML
#Airflow
#Compute Allocation
Data Engineer
•
System Design
•
hard
How would you design a distributed web scraper to crawl millions of specific domains daily, ensuring data freshness while respecting robots.txt and avoiding IP bans?
#Web Scraping
#Distributed Queues
#Proxies
#Politeness
Data Engineer
•
System Design
•
hard
Design a real-time monitoring system for ChatGPT API latency and error rates. The system needs to aggregate metrics per minute, per user tier, and per model, handling millions of requests per second.
#Stream Processing
#Kafka
#Time-Series Databases
#High Throughput
Data Engineer
•
System Design
•
hard
Design an ETL pipeline that takes newly published research papers, generates embeddings using our API, and updates a vector database for RAG (Retrieval-Augmented Generation) without causing downtime.
#ETL
#Vector Databases
#Embeddings
#Idempotency
Data Engineer
•
Technical
•
medium
What are the trade-offs between Parquet and JSONL formats for storing LLM training data?
#File Formats
#Parquet
#JSONL
#Compression
Data Engineer
•
Technical
•
medium
Compare and contrast using Parquet vs. Avro vs. JSONL for storing our intermediate model checkpoints and training datasets. Which would you choose for a read-heavy analytical workload vs. a write-heavy logging workload?
#File Formats
#Parquet
#Avro
#Optimization
Data Engineer
•
Technical
•
hard
How would you design a system to automatically detect and filter out PII (Personally Identifiable Information) from a continuous stream of training data before it hits our secure storage?
#Data Privacy
#PII
#Stream Processing
#Machine Learning
Data Engineer
•
Technical
•
medium
Explain how you would optimize a PySpark job that is experiencing severe data skew during a join operation between a massive table of web documents and a smaller table of domain reputation scores.
#Spark
#Performance Tuning
#Distributed Computing
Data Engineer
•
Technical
•
medium
Describe how you would ensure idempotency in a data pipeline that processes billing events for OpenAI API usage, ensuring no user is double-charged in case of pipeline retries.
#Idempotency
#Data Pipelines
#Transactional Systems
Data Engineer
•
Technical
•
hard
OpenAI uses Ray heavily for distributed computing. Explain how Ray's architecture differs from Apache Spark, and in what scenarios Ray is a better choice for data processing.
#Ray
#Apache Spark
#Architecture
#ML Workloads
Data Engineer
•
Technical
•
medium
Explain the differences between Parquet and Avro formats. In what specific scenarios would you choose one over the other for storing tokenized LLM training data?
#File Formats
#Parquet
#Avro
#Columnar vs Row
Data Engineer
•
Technical
•
hard
What heuristics, statistical methods, and ML-based approaches would you use to detect and filter out low-quality, toxic, or repetitive text from a pre-training dataset?
#NLP
#Data Cleaning
#Heuristics
#Machine Learning
Data Engineer
•
Technical
•
hard
Given a table of user interactions, write a query to calculate the session length for each user, where a session ends after 30 minutes of inactivity.
#Sessionization
#Window Functions
#CTEs
Data Engineer
•
Technical
•
hard
How would you optimize a slow-running SQL query that joins a massive `api_logs` table with a `users` table, where the `api_logs` table is highly skewed?
#Query Optimization
#Data Skew
#Joins
Data Engineer
•
Technical
•
medium
Write a query to find the daily retention rate of users who used a specific model (e.g., GPT-4) in their first week.
#Cohorts
#Retention
#Self Joins
Data Engineer
•
Technical
•
hard
Describe the algorithmic and infrastructural differences between implementing exact deduplication versus fuzzy deduplication on a petabyte-scale text dataset.
#Deduplication
#Hashing
#LSH
#Scale
Data Engineer
•
Technical
•
hard
Write a SQL query to identify 'bursty' API users—those who consume more than 10x their daily average tokens within a single hour.
#Advanced Aggregations
#Window Functions
#Time Series
Data Engineer
•
Technical
•
hard
Explain how you would handle an OutOfMemory (OOM) error in a Spark job processing a highly skewed dataset.
#Apache Spark
#OOM
#Data Skew
#Performance Tuning
Data Engineer
•
Technical
•
medium
Compare and contrast Apache Spark and Ray. When would you choose Ray over Spark for data processing at OpenAI?
#Apache Spark
#Ray
#Architecture
#Machine Learning
Data Engineer
•
Technical
•
hard
How do you ensure exactly-once processing semantics in a Kafka to Spark Streaming pipeline?
#Kafka
#Spark Streaming
#Exactly-Once
#Checkpoints
Data Engineer
•
Technical
•
medium
Describe your strategy for partitioning a massive Delta Lake table containing daily chat logs to optimize for both point-in-time and user-specific queries.
#Delta Lake
#Partitioning
#Z-Ordering
#Storage Optimization
Data Engineer
•
Technical
•
medium
Write a SQL query to find the top 1% of users by token consumption over the last 30 days, partitioned by pricing tier.
#Window Functions
#Percentiles
#Aggregations
Data Engineer
•
Technical
•
medium
How would you implement a backfill strategy for a data pipeline that calculates daily active users, if the logic changed and needs to be applied to the last 2 years of data?
#Backfilling
#Airflow
#Idempotency
#ETL
Data Engineer
•
Technical
•
medium
Explain how Broadcast Joins work in Spark and when they should be avoided.
#Apache Spark
#Joins
#Optimization
Data Engineer
•
Technical
•
medium
How do you monitor and alert on data drift in a pipeline feeding a machine learning model?
#Data Drift
#Monitoring
#MLOps
#Statistics
Data Engineer
•
Technical
•
medium
Your Spark job processing tokenized text is experiencing frequent OutOfMemory (OOM) errors during a shuffle phase. Walk me through your debugging and optimization steps.
#Apache Spark
#Memory Management
#Debugging
Data Engineer
•
Technical
•
medium
What metrics would you track to ensure the quality of a web-scraped dataset intended for model training?
#Data Quality
#Metrics
#NLP
Data Engineer
•
Technical
•
hard
How do you handle schema evolution in a streaming data pipeline without breaking downstream consumers?
#Schema Evolution
#Streaming
#Avro
#Protobuf
Data Engineer
•
Technical
•
medium
Design an idempotency mechanism for a data pipeline that occasionally fails and retries midway through processing.
#Idempotency
#ETL
#Fault Tolerance
Data Engineer
•
Technical
•
hard
Explain how you would handle severe data skew in a Spark join operation involving a massive table of user prompts and a smaller table of flagged safety keywords.
#Apache Spark
#Data Skew
#Performance Tuning
Data Scientist
•
Behavioral
•
medium
OpenAI moves extremely fast. Tell me about a time you had to trade off rigorous statistical methodology for speed of execution.
#Speed vs Quality
#Pragmatism
#Execution
Data Scientist
•
Behavioral
•
medium
Tell me about a time you had to make a critical product or technical decision with highly ambiguous or incomplete data.
#Ambiguity
#Decision Making
#Risk Management
Data Scientist
•
Behavioral
•
medium
Tell me about a time you had to pivot your research or analysis because your initial hypothesis was completely invalidated by the data. How did you communicate this to stakeholders?
#Adaptability
#Communication
#Truth-seeking
Data Scientist
•
Behavioral
•
medium
Describe a time you disagreed with an engineering lead or product manager about launching a model feature due to safety, bias, or data quality concerns. How did you resolve it?
#Conflict Resolution
#AI Safety
#Stakeholder Management
Data Scientist
•
Behavioral
•
hard
What is the most complex data problem you have solved end-to-end, and what was the ultimate business impact of your solution?
#End-to-End Ownership
#Impact
#Technical Depth
Data Scientist
•
Behavioral
•
medium
Describe a project where you had to collaborate closely with engineering to get your data pipelines or ML models into production.
#Collaboration
#MLOps
#Productionization
Data Scientist
•
Behavioral
•
medium
Tell me about a time you had to learn a completely new technical domain (e.g., a new ML architecture or infrastructure tool) in a very short amount of time to deliver a project.
#Adaptability
#Learning Agility
#Curiosity
Data Scientist
•
Behavioral
•
medium
OpenAI's mission is to ensure AGI benefits all of humanity. How does this mission influence your day-to-day work and decision-making as a Data Scientist?
#Mission Alignment
#Ethics
#Safety
Data Scientist
•
Behavioral
•
easy
How do you prioritize your work when you have multiple urgent, high-impact requests from different research and product teams?
#Prioritization
#Time Management
#Cross-functional
Data Scientist
•
Behavioral
•
medium
Tell me about a time you discovered a critical flaw in your own analysis after it had already been shared with leadership or stakeholders.
#Integrity
#Accountability
#Continuous Improvement
Data Scientist
•
Behavioral
•
medium
Describe a situation where you strongly disagreed with a product manager or engineering lead about a metric or experiment result. How did you resolve it?
#Conflict Resolution
#Communication
#Stakeholder Management
Data Scientist
•
Coding
•
medium
Given a list of user sessions containing timestamps and generated token counts, write an algorithm in Python to classify sessions as 'bot/scraper' vs. 'human' based on generation cadence and prompt frequency.
#Anomaly Detection
#Time Series
#Python
Data Scientist
•
Coding
•
medium
Write a SQL query to find the top 1% of OpenAI API users by token volume who also have an error rate (e.g., HTTP 429 Rate Limit) exceeding 20% over the last 7 days.
#Percentiles
#Aggregations
#API Metrics
Data Scientist
•
Coding
•
hard
Implement a stratified sampling algorithm in Python to select prompt-response pairs for human evaluation (RLHF), ensuring proportional representation across 50 languages and 20 topic categories.
#Sampling
#Probability
#Data Structures
Data Scientist
•
Coding
•
medium
Write a Python function to parse a massive JSONL file of ChatGPT conversation logs (too large to fit in memory) and compute the rolling 7-day average of messages per session.
#Data Generators
#Memory Management
#Time Series
Data Scientist
•
Coding
•
medium
Using SQL, find the top 1% of API users by total token consumption over the last 30 days who also have a prompt-to-completion token ratio greater than 5:1.
#Percentiles
#Aggregations
#Filtering
Data Scientist
•
Coding
•
medium
Write a SQL query to calculate the week-over-week retention rate of ChatGPT Plus users who utilized the Advanced Data Analysis feature within their first 3 days of upgrading.
#Retention
#Window Functions
#Cohorts
Data Scientist
•
Coding
•
medium
Write a SQL query to calculate the week-over-week rolling retention rate for ChatGPT Plus subscribers, specifically isolating users who upgraded from the free tier within the last 30 days.
#Window Functions
#Cohorts
#User Retention
Data Scientist
•
Coding
•
hard
Given a stream of incoming API requests represented as tuples of (timestamp, user_id, token_count), write a Python algorithm to identify users who are consistently hitting the 99th percentile of token usage within any rolling 5-minute window.
#Streaming Data
#Sliding Window
#Heaps/Queues
Data Scientist
•
Coding
•
hard
Design a SQL query to detect potential API key sharing by identifying accounts with requests originating from more than 5 distinct IP addresses within a rolling 10-minute window.
#Self-Joins
#Rolling Windows
#Anomaly Detection
Data Scientist
•
System Design
•
hard
Design a data pipeline to continuously update the knowledge cutoff of an LLM using web search data and news feeds.
#Data Pipelines
#Web Scraping
#Data Quality
Data Scientist
•
System Design
•
medium
Design an analytics dashboard backend for OpenAI Enterprise customers to monitor their organization's usage, costs, and ROI.
#Data Modeling
#Multi-tenancy
#OLAP
Data Scientist
•
System Design
•
hard
How would you design a system to detect and mitigate prompt injection attacks at scale before they hit the main inference cluster?
#Security
#Classification
#System Architecture
Data Scientist
•
System Design
•
hard
Design the telemetry and analytics pipeline to track token usage, latency, and error rates for the OpenAI API in real-time.
#Streaming Architecture
#Telemetry
#Scalability
Data Scientist
•
System Design
•
hard
Design a telemetry data pipeline to capture, process, and analyze user feedback (thumbs up/down and text corrections) on ChatGPT responses in real-time to trigger alerts for model degradation.
#Real-time Processing
#Streaming Architecture
#Data Pipelines
Data Scientist
•
System Design
•
hard
Design a system to monitor, detect, and alert on API latency degradation specifically for enterprise customers using provisioned throughput, ensuring a false positive rate of less than 1%.
#Monitoring
#Anomaly Detection
#Enterprise SLAs
Data Scientist
•
Technical
•
medium
How would you identify and mitigate bias in a dataset used to fine-tune our moderation endpoint to ensure it doesn't disproportionately flag text from specific demographic dialects?
#Bias Mitigation
#Data Quality
#Content Moderation
Data Scientist
•
Technical
•
hard
We are considering introducing a new pricing tier for the API based on compute time rather than purely on token count. How would you model the financial impact and predict user churn?
#Pricing Models
#Forecasting
#Churn Prediction
Data Scientist
•
Technical
•
hard
How do you determine the required sample size for a prompt-variation A/B test when the primary evaluation metric is subjective human preference (e.g., Elo rating)?
#Power Analysis
#Elo Ratings
#Variance Estimation
Data Scientist
•
Technical
•
hard
Explain the statistical and practical trade-offs between using Reinforcement Learning from Human Feedback (RLHF) versus Direct Preference Optimization (DPO) for aligning a language model.
#RLHF
#DPO
#Model Alignment
Data Scientist
•
Technical
•
medium
ChatGPT Daily Active Users (DAU) dropped by 5% week-over-week, but API usage increased by 10%. Walk me through your diagnostic process to find the root cause.
#Root Cause Analysis
#Metric Trees
#Cannibalization
Data Scientist
•
Technical
•
hard
We are A/B testing a new UI feature on ChatGPT that allows users to share interactive conversation snippets. How would you design the experiment to account for network effects and spillover?
#A/B Testing
#Network Effects
#Experiment Design
Data Scientist
•
Technical
•
hard
How would you design an automated evaluation metric to detect and quantify hallucinations in a new iteration of the GPT-4 model without relying entirely on human annotators?
#LLM Evaluation
#Hallucination Detection
#Auto-Evals
Data Scientist
•
Technical
•
hard
How would you design an A/B test to evaluate a new model routing algorithm (e.g., dynamically routing between GPT-4o and GPT-4-turbo) where the primary metric is perceived user latency?
#Experiment Design
#Latency Metrics
#Trade-offs
Data Scientist
•
Technical
•
hard
ChatGPT responses are highly non-deterministic. How do you measure the statistical significance of a system prompt change on overall response quality?
#Variance Reduction
#LLM Evaluation
#Hypothesis Testing
Data Scientist
•
Technical
•
hard
Explain how you would handle network effects in an A/B test for a new collaborative workspace feature in ChatGPT Enterprise.
#Network Effects
#Cluster Randomization
#Enterprise Analytics
Data Scientist
•
Technical
•
medium
We want to introduce a new dynamic usage cap for GPT-4 based on server load. How would you determine the optimal threshold to minimize user churn while maximizing compute savings?
#Optimization
#Churn Prediction
#Capacity Planning
Data Scientist
•
Technical
•
medium
What metrics would you define to evaluate the success and adoption of the 'Custom Instructions' feature in ChatGPT?
#Metric Definition
#Product Sense
#User Engagement
Data Scientist
•
Technical
•
medium
You run an A/B test on a new moderation endpoint. The false positive rate drops by 2%, but latency increases by 50ms. How do you decide whether to ship it?
#Trade-offs
#Decision Making
#Safety
Data Scientist
•
Technical
•
hard
How would you estimate the cannibalization effect of releasing a cheaper, faster model (like GPT-4o mini) on our flagship model's API revenue?
#Causal Inference
#Cannibalization
#Forecasting
Data Scientist
•
Technical
•
hard
How do you evaluate the quality of text embeddings generated by our API without relying entirely on downstream task performance?
#Embeddings
#Unsupervised Evaluation
#NLP
Data Scientist
•
Technical
•
hard
Explain the trade-offs between using RLHF (Reinforcement Learning from Human Feedback) versus DPO (Direct Preference Optimization) from a data collection and evaluation standpoint.
#RLHF
#DPO
#Model Alignment
Data Scientist
•
Technical
•
hard
How would you build an automated metric to quantify 'hallucinations' in a RAG-based enterprise deployment?
#Hallucination Detection
#RAG
#LLM-as-a-judge
Data Scientist
•
Technical
•
hard
We notice a degradation in coding performance (e.g., HumanEval scores) in the latest model checkpoint. How do you investigate if this is a real regression or an artifact of the evaluation set?
#Model Evaluation
#Debugging
#Data Contamination
Data Scientist
•
Technical
•
hard
Describe how you would design a reward model for a specific domain, like medical advice, where accuracy is critical but human raters might frequently disagree.
#Reward Models
#Data Annotation
#Domain Expertise
Data Scientist
•
Technical
•
medium
What is perplexity, and why is it sometimes a misleading metric for evaluating the final conversational quality of an aligned LLM?
#Perplexity
#Information Theory
#Model Alignment
Data Scientist
•
Technical
•
medium
How would you cluster millions of user prompts to identify emerging use cases for ChatGPT without manually labeling the data?
#Clustering
#Topic Modeling
#Unsupervised Learning
Data Scientist
•
Technical
•
hard
If we want to personalize the ChatGPT experience based on past interactions, what data points would you use and how would you evaluate the risk of catastrophic forgetting in the model?
#Personalization
#Continual Learning
#Memory
Data Scientist
•
Technical
•
hard
Walk me through how you would price a new multimodal API endpoint (e.g., video generation). What data do you need to make this decision?
#Pricing Strategy
#Unit Economics
#Market Analysis
Data Scientist
•
Technical
•
medium
ChatGPT Daily Active Users (DAU) is dropping in a specific region. Walk me through your diagnostic process to identify the root cause.
#Root Cause Analysis
#Product Metrics
#Debugging
DevOps Engineer
•
Behavioral
•
medium
Tell me about a time you had to debug a critical production outage under extreme pressure. What was your process?
#Incident Response
#Debugging
#Communication
DevOps Engineer
•
Behavioral
•
medium
OpenAI moves incredibly fast. Tell me about a time you had to make a trade-off between doing something 'the right way' and doing it quickly to meet a critical business need.
#Trade-offs
#Technical Debt
#Prioritization
DevOps Engineer
•
Behavioral
•
medium
Describe a situation where you disagreed with a machine learning researcher or software engineer about infrastructure architecture. How did you resolve it?
#Conflict Resolution
#Collaboration
#Empathy
DevOps Engineer
•
Behavioral
•
easy
Tell me about a time you automated a tedious process that saved your team significant time.
#Automation
#Initiative
#Impact
DevOps Engineer
•
Behavioral
•
medium
Tell me about a time you discovered a significant security vulnerability or misconfiguration in your infrastructure. How did you handle it?
#Security
#Incident Response
#Integrity
DevOps Engineer
•
Coding
•
medium
Write a script to parse a massive, 500GB log file to find the top 10 IP addresses making requests, optimized for memory constraints.
#File I/O
#Data Structures
#Memory Management
#Streaming
DevOps Engineer
•
Coding
•
medium
Implement a basic load balancer in Python that distributes incoming requests to a list of backend servers using a weighted round-robin algorithm.
#Load Balancing
#Math
#Data Structures
DevOps Engineer
•
Coding
•
hard
Write a concurrent Go program (or Python with asyncio) to ping 10,000 endpoints and return a list of unreachable ones within a strict 5-second timeout.
#Concurrency
#Networking
#Goroutines
#Asyncio
DevOps Engineer
•
Coding
•
medium
Write a function to check if a given CIDR block overlaps with a list of existing CIDR blocks in a VPC.
#Networking
#Bit Manipulation
#IP Addressing
DevOps Engineer
•
Coding
•
medium
Given a list of server dependencies (e.g., A depends on B, B depends on C), write a script to determine the correct startup order.
#Graphs
#Topological Sort
#DFS/BFS
DevOps Engineer
•
Coding
•
medium
Implement a token bucket rate limiter in Go or Python that can be used across a distributed system.
#Concurrency
#Distributed Systems
#Redis
DevOps Engineer
•
System Design
•
hard
Design a system to securely distribute multi-gigabyte model weights to thousands of edge inference nodes globally with minimal latency and network cost.
#Content Delivery
#Peer-to-Peer
#Security
#Edge Computing
DevOps Engineer
•
System Design
•
hard
Design a distributed checkpointing system for large-scale model training that needs to write terabytes of state data every 10 minutes without blocking GPU execution.
#Distributed Systems
#Storage
#High Throughput
#GPU Infrastructure
DevOps Engineer
•
System Design
•
hard
Design an auto-scaling system for inference nodes based on custom metrics like queue depth and GPU memory fragmentation, rather than just CPU usage.
#Auto-scaling
#Custom Metrics
#KEDA
#Capacity Planning
DevOps Engineer
•
System Design
•
medium
Design a highly available internal DNS architecture for a multi-region cloud environment that supports millions of internal queries per second.
#DNS
#Networking
#High Availability
DevOps Engineer
•
System Design
•
hard
Design a high-throughput, low-latency API gateway for LLM inference that handles streaming responses (e.g., Server-Sent Events).
#API Gateway
#Load Balancing
#Streaming
#WebSockets/SSE
DevOps Engineer
•
System Design
•
hard
Design a centralized logging architecture capable of ingesting petabytes of logs per day from distributed inference servers with sub-minute search latency.
#Logging
#Big Data
#Elasticsearch
#Kafka
DevOps Engineer
•
System Design
•
medium
Design a CI/CD pipeline for deploying a microservice that serves a new machine learning model to millions of users, ensuring zero downtime.
#Deployment Strategies
#Canary Releases
#Rollbacks
#Testing
DevOps Engineer
•
Technical
•
hard
How would you design a disaster recovery plan for a cloud-native LLM application relying heavily on managed cloud services (e.g., Azure Cosmos DB, Blob Storage)?
#Disaster Recovery
#Azure
#RTO/RPO
#High Availability
DevOps Engineer
•
Technical
•
medium
How do you handle database schema migrations in a zero-downtime CI/CD pipeline?
#CI/CD
#Database Migrations
#Zero Downtime
DevOps Engineer
•
Technical
•
medium
Walk me through the exact lifecycle of a Kubernetes pod from the moment `kubectl apply` is executed to when the container is running.
#Kubernetes Architecture
#API Server
#Kubelet
#Scheduler
DevOps Engineer
•
Technical
•
hard
Explain how Prometheus handles high cardinality data and how you would mitigate a cardinality explosion caused by a misconfigured label.
#Prometheus
#TSDB
#Monitoring
DevOps Engineer
•
Technical
•
hard
How do you secure a multi-tenant Kubernetes cluster where different research teams need strict compute and network isolation?
#Kubernetes Security
#Network Policies
#RBAC
#Multi-tenancy
DevOps Engineer
•
Technical
•
medium
How do you implement blue-green deployments for a stateful application backed by a relational database?
#Deployment Strategies
#Databases
#Stateful Applications
DevOps Engineer
•
Technical
•
hard
How do you handle Kubernetes node failures in a cluster running long-lived, stateful GPU training jobs?
#Kubernetes
#Fault Tolerance
#StatefulSets
#GPU Scheduling
DevOps Engineer
•
Technical
•
hard
What is eBPF, and how can it be used for network observability and security in a high-throughput microservices architecture?
#eBPF
#Linux Kernel
#Observability
#Cilium
DevOps Engineer
•
Technical
•
medium
Explain the role of a Service Mesh (like Istio or Linkerd). What specific problems does it solve, and what overhead does it introduce?
#Service Mesh
#Microservices
#mTLS
#Traffic Management
DevOps Engineer
•
Technical
•
hard
What are the challenges of using Terraform with hundreds of developers, and how do you structure the repositories and state files to prevent bottlenecks?
#Terraform
#Scaling Teams
#Architecture
DevOps Engineer
•
Technical
•
easy
Explain the difference between Kubernetes Deployments, StatefulSets, and DaemonSets. When would you use each for AI workloads?
#Kubernetes Resources
#Workload Management
DevOps Engineer
•
Technical
•
medium
Explain how you would optimize Docker image builds for a massive Python monorepo to reduce CI times from 45 minutes to under 10 minutes.
#Docker
#CI/CD
#Caching
#Monorepo
DevOps Engineer
•
Technical
•
medium
How does Terraform handle state lock, and what exactly happens if the state file gets corrupted during a massive infrastructure rollout?
#Terraform
#State Management
#Disaster Recovery
DevOps Engineer
•
Technical
•
hard
Describe how you would monitor and alert on GPU utilization, memory bottlenecks, and interconnect health across a 10,000-node cluster.
#Prometheus
#DCGM
#GPU Monitoring
#Alerting
DevOps Engineer
•
Technical
•
medium
How do you troubleshoot a 'CrashLoopBackOff' error in Kubernetes, specifically if the pod contains a GPU-bound container that fails silently?
#Debugging
#Containers
#GPU
DevOps Engineer
•
Technical
•
hard
What is InfiniBand, and how does RDMA differ from traditional TCP/IP networking in the context of distributed model training?
#InfiniBand
#RDMA
#TCP/IP
#High Performance Computing
DevOps Engineer
•
Technical
•
medium
How do you manage and rotate secrets in a multi-tenant Kubernetes environment at scale without restarting pods?
#Kubernetes
#Secret Management
#Vault
#Security
Frontend Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a product manager or designer about a user experience decision. How did you resolve it?
#Conflict Resolution
#Collaboration
#User Empathy
Frontend Engineer
•
Behavioral
•
easy
Why do you want to work at OpenAI? How do you align with our mission to ensure that artificial general intelligence benefits all of humanity?
#Mission Alignment
#Motivation
#AI Safety
Frontend Engineer
•
Behavioral
•
medium
Tell me about a time you had to build a complex UI feature with highly ambiguous requirements. How did you determine what to build?
#Ambiguity
#Product Sense
#Communication
Frontend Engineer
•
Behavioral
•
medium
Give an example of a complex technical problem you solved that required you to learn a completely new technology or framework on the fly.
#Adaptability
#Learning
#Problem Solving
Frontend Engineer
•
Behavioral
•
medium
Describe a situation where you had to make a difficult trade-off between shipping quickly and writing perfect, scalable code. What was the outcome?
#Trade-offs
#Delivery
#Technical Debt
Frontend Engineer
•
Coding
•
medium
Write a function to find the shortest path between two DOM elements in the DOM tree (i.e., finding their lowest common ancestor and the path to it).
#DOM API
#Tree Traversal
#Pointers
Frontend Engineer
•
Coding
•
hard
Implement a function that schedules tasks with a maximum concurrency limit. It should take an array of functions (returning promises) and a concurrency number.
#Promises
#Concurrency
#Queues
Frontend Engineer
•
Coding
•
medium
Write a custom React hook `useFetch` that takes a URL and options. It should handle loading state, error state, caching responses, and aborting the request if the component unmounts.
#React Hooks
#Network
#AbortController
Frontend Engineer
•
Coding
•
medium
Implement an Event Emitter class with `on`, `off`, `once`, and `emit` methods.
#Design Patterns
#Data Structures
#Context
Frontend Engineer
•
Coding
•
easy
Write a function to traverse the DOM tree starting from a given node and return an array of all text nodes that match a specific regular expression.
#DOM API
#Tree Traversal
#Recursion
Frontend Engineer
•
Coding
•
medium
Write a debounce function that includes an `immediate` flag, allowing the function to trigger immediately on the first call and then debounce subsequent calls.
#Closures
#Timers
#Higher-Order Functions
Frontend Engineer
•
Coding
•
hard
Implement a virtualized list component from scratch in React to render a chat history with 100,000 messages of variable heights.
#Performance
#DOM Manipulation
#React
Frontend Engineer
•
Coding
•
hard
Write a function to parse and render a continuous stream of Markdown text. How do you handle incomplete Markdown tokens (e.g., a code block that has started with '```' but hasn't closed yet)?
#Parsing
#String Manipulation
#Edge Cases
Frontend Engineer
•
Coding
•
medium
Write a function that takes a string of HTML and returns true if the tags are properly balanced and nested, and false otherwise.
#Stacks
#String Parsing
#Regex
Frontend Engineer
•
Coding
•
medium
Implement a custom `Promise.allSettled` function from scratch.
#Promises
#Asynchronous JavaScript
#Error Handling
Frontend Engineer
•
Coding
•
medium
Implement a rate-limit UI component. When a user hits a rate limit (e.g., GPT-4 usage cap), the submit button should disable and show a live countdown timer until they can prompt again.
#React
#Time Management
#State Management
Frontend Engineer
•
Coding
•
medium
Write a function to deeply merge two JavaScript objects. It should handle nested objects, arrays, and edge cases like null or undefined.
#Recursion
#Data Structures
#Type Checking
Frontend Engineer
•
Coding
•
medium
Implement an LRU (Least Recently Used) Cache class in JavaScript. It should have `get(key)` and `put(key, value)` methods, both operating in O(1) time complexity.
#Data Structures
#Hash Maps
#Linked Lists
Frontend Engineer
•
Coding
•
hard
Implement a rich text editor component that supports @mentions. When a user types '@', a dropdown should appear to select different AI models (e.g., GPT-3.5, GPT-4).
#DOM Manipulation
#Event Handling
#Positioning
Frontend Engineer
•
Coding
•
medium
Implement a custom React hook `useStreamingResponse(url, prompt)` that connects to an SSE endpoint, accumulates the streamed text chunks, and returns the current text and a boolean indicating if the stream is complete.
#React Hooks
#Server-Sent Events
#Asynchronous JavaScript
Frontend Engineer
•
Coding
•
hard
Write a function to serialize a DOM tree into a JSON object, and another function to deserialize that JSON object back into a DOM tree.
#DOM API
#Serialization
#Recursion
Frontend Engineer
•
Coding
•
hard
Implement a basic reactive state system (similar to Vue or MobX) using JavaScript Proxies. When a property on the state object is accessed, register the current observer. When it is mutated, trigger the observers.
#Proxies
#Design Patterns
#Reactivity
Frontend Engineer
•
System Design
•
medium
Design a robust telemetry and error tracking system for the frontend. How do you capture unhandled exceptions, promise rejections, and performance metrics without impacting the user experience?
#Observability
#Error Handling
#Performance
Frontend Engineer
•
System Design
•
medium
Design the architecture for a 'Shared Chat' feature, where a user can generate a public URL for a specific conversation. Consider security, SEO, and hydration.
#Next.js
#SSR
#Security
#SEO
Frontend Engineer
•
System Design
•
medium
Design an image gallery for DALL-E generations. It needs to support infinite scrolling, lazy loading of high-res images, and a masonry layout.
#Layout
#Performance
#Intersection Observer
Frontend Engineer
•
System Design
•
hard
Design a real-time collaborative prompt engineering playground where multiple users can edit a prompt simultaneously and see live model outputs.
#WebSockets
#Operational Transformation (OT)
#CRDTs
#Concurrency
Frontend Engineer
•
System Design
•
hard
Design a robust file upload system for the Advanced Data Analysis (Code Interpreter) feature. It must handle files up to 1GB, support resume on failure, and show progress.
#Chunked Uploads
#Network Resilience
#File API
Frontend Engineer
•
System Design
•
hard
Design the frontend architecture for the ChatGPT web client. Focus specifically on how you would handle streaming responses, manage conversation state, and handle network interruptions.
#Architecture
#Streaming
#State Management
#Resilience
Frontend Engineer
•
System Design
•
hard
Design a canvas-based node editor (similar to a visual workflow builder for chaining LLM prompts). How do you handle rendering, zooming, panning, and connecting nodes?
#Canvas API
#WebGL
#Math
#State Management
Frontend Engineer
•
Technical
•
medium
What are the security implications of rendering user-generated or AI-generated Markdown into HTML? How do you prevent XSS attacks in a React application?
#XSS
#Sanitization
#React
Frontend Engineer
•
Technical
•
hard
How would you optimize the performance of a React application that frequently updates a large, complex SVG (e.g., a real-time data visualization of model weights)?
#React
#SVG
#Rendering Optimization
Frontend Engineer
•
Technical
•
medium
Explain the differences between WebSockets, Server-Sent Events (SSE), and Long Polling. Why does ChatGPT primarily use SSE for model responses?
#Networking
#Protocols
#Performance
Frontend Engineer
•
Technical
•
medium
What are the accessibility (a11y) considerations when building a dynamically updating chat interface like ChatGPT?
#ARIA
#Screen Readers
#UX
Frontend Engineer
•
Technical
•
hard
How does React 18's concurrent rendering work? How would you use `useTransition` or `useDeferredValue` to keep a chat interface responsive while rendering a heavy Markdown response?
#React Internals
#Performance Optimization
#Concurrency
Frontend Engineer
•
Technical
•
medium
Explain the JavaScript event loop, microtasks, and macrotasks. How does a heavy DOM update impact the event loop, and how can you mitigate it?
#Event Loop
#Performance
#Browser Architecture
Full Stack Engineer
•
Behavioral
•
hard
How do you balance the need for rapid iteration and shipping features quickly with the necessity of maintaining rigorous AI safety, privacy, and security standards?
#Ethics
#Security
#Productivity
Full Stack Engineer
•
Behavioral
•
medium
Describe a situation where you disagreed with a product manager or AI researcher about the technical direction of a feature. How did you resolve it?
#Communication
#Conflict Resolution
#Collaboration
Full Stack Engineer
•
Behavioral
•
medium
Tell me about a time you had to ship a feature under extreme time pressure. What technical corners did you cut, and how did you manage the resulting technical debt?
#Delivery
#Technical Debt
#Prioritization
Full Stack Engineer
•
Behavioral
•
hard
Tell me about a complex production incident you debugged. What was the root cause, and what specific steps did you take to prevent it from happening again?
#Incident Management
#Debugging
#Post-mortems
Full Stack Engineer
•
Behavioral
•
medium
Describe a time you took ownership of a poorly defined problem or ambiguous feature request and drove it to successful completion.
#Ownership
#Ambiguity
#Execution
Full Stack Engineer
•
Behavioral
•
medium
OpenAI moves incredibly fast. Tell me about a time you had to pivot your technical approach halfway through a project due to changing requirements or new model capabilities.
#Adaptability
#Agile
#Resilience
Full Stack Engineer
•
Behavioral
•
easy
Tell me about a time you had to learn a completely new technology, framework, or domain on the fly to deliver a critical project.
#Learning
#Adaptability
#Growth Mindset
Full Stack Engineer
•
Coding
•
hard
Implement a simplified Byte Pair Encoding (BPE) token counting algorithm that calculates the number of tokens in a given string based on a provided vocabulary dictionary.
#Strings
#Greedy Algorithms
#NLP
Full Stack Engineer
•
Coding
•
medium
Write a function to traverse a DOM tree and extract all visible text, simulating how a web scraper plugin might extract context for an LLM.
#DOM Manipulation
#Recursion
#Trees
Full Stack Engineer
•
Coding
•
medium
Implement a concurrent task runner in TypeScript that processes an array of async tasks but limits the maximum number of active promises to a given concurrency limit.
#TypeScript
#Promises
#Concurrency
Full Stack Engineer
•
Coding
•
medium
Implement a React component that consumes a Server-Sent Events (SSE) endpoint to display a streaming chat response, similar to ChatGPT.
#React
#SSE
#Streaming
#State Management
Full Stack Engineer
•
Coding
•
hard
Write a rate limiter in Python using Redis to handle OpenAI API tier limits, specifically enforcing both tokens per minute (TPM) and requests per minute (RPM).
#Python
#Redis
#Rate Limiting
#Concurrency
Full Stack Engineer
•
Coding
•
medium
Implement an LRU cache with a time-to-live (TTL) feature. If an item expires, it should not be returned, and it should be evicted.
#Data Structures
#Hash Map
#Linked List
Full Stack Engineer
•
Coding
•
medium
Design a function to merge overlapping text highlights in a document. Given an array of intervals [start, end], return an array of non-overlapping intervals.
#Arrays
#Sorting
#Intervals
Full Stack Engineer
•
Coding
•
medium
Write a Python script using asyncio to fetch data from multiple LLM endpoints concurrently, aggregate the results, and return early if any request exceeds a 2-second timeout.
#Python
#asyncio
#Concurrency
#API Integration
Full Stack Engineer
•
Coding
•
easy
Create a custom React hook `useDebounce` and implement it within an autocomplete search input for querying a prompt library.
#React
#Hooks
#Performance
Full Stack Engineer
•
Coding
•
easy
Given a raw text string representing a conversation, parse it into a structured JSON format of roles (system, user, assistant) and content blocks.
#String Manipulation
#Parsing
#Regex
Full Stack Engineer
•
System Design
•
medium
Design a system to handle webhooks for OpenAI API fine-tuning jobs, ensuring at-least-once delivery and handling downstream customer endpoint failures.
#Webhooks
#Message Queues
#Retry Logic
#Distributed Systems
Full Stack Engineer
•
System Design
•
hard
Design the architecture for ChatGPT's web interface, focusing on real-time streaming, chat history persistence, and state management across multiple devices.
#Architecture
#Streaming
#State Management
#Databases
Full Stack Engineer
•
System Design
•
hard
Design an API gateway that routes requests to different model endpoints (e.g., GPT-3.5, GPT-4) based on load, availability, and user subscription tier.
#API Gateway
#Load Balancing
#Routing
#High Availability
Full Stack Engineer
•
System Design
•
hard
How would you architect a system to securely store, process, and manage user-uploaded files for the Advanced Data Analysis (Code Interpreter) feature?
#Security
#Storage
#Sandboxing
#Microservices
Full Stack Engineer
•
System Design
•
hard
Design a distributed rate limiting system for the OpenAI API that enforces both Requests Per Minute (RPM) and Tokens Per Minute (TPM) globally across multiple data centers.
#Distributed Systems
#Rate Limiting
#Redis
#Eventual Consistency
Full Stack Engineer
•
System Design
•
hard
Design a real-time collaborative prompt playground where multiple users can edit a prompt simultaneously and see model outputs, similar to Google Docs.
#WebSockets
#CRDTs
#Operational Transformation
#Real-time
Full Stack Engineer
•
System Design
•
hard
Architect a plugin execution engine that safely calls third-party APIs based on LLM outputs while preventing Server-Side Request Forgery (SSRF) and timing attacks.
#Security
#API Integration
#Network Architecture
Full Stack Engineer
•
System Design
•
medium
Design the database schema and backend architecture for storing and retrieving user chat histories with minimal latency, considering users might have thousands of long conversations.
#Database Design
#Indexing
#NoSQL
#Caching
Full Stack Engineer
•
System Design
•
hard
How would you design a scalable prompt evaluation platform where enterprise users can run A/B tests on different LLM prompts across millions of dataset rows?
#Batch Processing
#Scalability
#Data Pipelines
#Analytics
Full Stack Engineer
•
System Design
•
medium
Design a logging and monitoring pipeline to track API latency, error rates, and token usage per customer in real-time.
#Observability
#Data Pipelines
#Metrics
#Elasticsearch/Prometheus
Full Stack Engineer
•
Technical
•
hard
How do you handle React state updates when receiving high-frequency streaming data (e.g., 50 chunks per second) without causing UI freezing or performance degradation?
#React
#Performance
#Rendering
Full Stack Engineer
•
Technical
•
hard
Describe your approach to testing a non-deterministic system, such as a UI component that relies on LLM-generated content which changes every time.
#QA
#Mocking
#E2E Testing
Full Stack Engineer
•
Technical
•
medium
Describe how you would implement optimistic UI updates for a chat application where the backend response might take several seconds to begin.
#UX
#State Management
#API Integration
Full Stack Engineer
•
Technical
•
medium
What are the security implications of rendering Markdown and HTML generated by an LLM, and how do you mitigate Cross-Site Scripting (XSS) attacks?
#Frontend Security
#XSS
#Sanitization
Full Stack Engineer
•
Technical
•
medium
Explain how you would manage database migrations in a high-traffic environment with zero downtime, specifically when adding a new column to a table with billions of rows.
#Database Administration
#Zero Downtime
#Migrations
Full Stack Engineer
•
Technical
•
medium
How does Python's Global Interpreter Lock (GIL) affect the performance of a multi-threaded web server, and how would you architect around it for a CPU-intensive task?
#Python
#Concurrency
#Multiprocessing
Full Stack Engineer
•
Technical
•
medium
Explain the differences between WebSockets, Server-Sent Events (SSE), and long polling. Why did OpenAI choose SSE for streaming ChatGPT responses?
#Networking
#Protocols
#Streaming
Full Stack Engineer
•
Technical
•
medium
How would you optimize a Python backend service that is heavily I/O bound due to waiting for model inference from GPU clusters?
#Python
#Performance
#Asynchronous Programming
Machine Learning Engineer
•
Behavioral
•
medium
What is the most challenging performance bottleneck you've ever optimized in a machine learning system? What tools did you use, and what was the impact?
#Performance Optimization
#Profiling
#Impact
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to debug a deeply complex, distributed system issue or a silent failure in a machine learning model. How did you isolate the root cause?
#Debugging
#Problem Solving
#Resilience
Machine Learning Engineer
•
Behavioral
•
medium
How do you balance AI safety and alignment with model performance and capabilities in your day-to-day engineering decisions?
#AI Safety
#Ethics
#Decision Making
Machine Learning Engineer
•
Behavioral
•
easy
Describe a project where you had to learn a completely new subfield of ML or systems engineering on the fly to deliver a critical feature.
#Adaptability
#Learning
#Ambiguity
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you had to pivot a major technical project because your initial approach fundamentally failed.
#Adaptability
#Problem Solving
#Resilience
Machine Learning Engineer
•
Behavioral
•
medium
OpenAI moves at an incredibly fast pace. Describe a situation where you had to ship a complex model or system under extreme time pressure with incomplete information.
#Time Management
#Prioritization
#Execution
Machine Learning Engineer
•
Behavioral
•
medium
OpenAI is focused on building safe AGI. How do you balance the need for rapid iteration and shipping product features with rigorous safety and alignment concerns?
#AI Safety
#Product Management
#Ethics
Machine Learning Engineer
•
Behavioral
•
medium
Tell me about a time you strongly disagreed with a senior researcher or engineer on the architectural direction of a model or system. How was it resolved?
#Conflict Resolution
#Communication
#Teamwork
Machine Learning Engineer
•
Coding
•
hard
Write a simple Autograd engine for scalar values from scratch. Implement the forward and backward passes for addition and multiplication.
#Calculus
#Graphs
#Object-Oriented Programming
Machine Learning Engineer
•
Coding
•
medium
Design a data structure for efficient KV cache eviction in an LLM serving engine. It must support O(1) inserts, O(1) lookups, and evict the least recently used sequence block.
#Data Structures
#Linked Lists
#Hash Maps
Machine Learning Engineer
•
Coding
•
hard
Write a function to perform matrix multiplication of two large 2D arrays. Optimize it for cache locality using block matrix multiplication (tiling).
#C++
#Performance Optimization
#Computer Architecture
Machine Learning Engineer
•
Coding
•
easy
Implement the Softmax function. Modify your implementation to ensure numerical stability when dealing with very large logits.
#Math
#Python
Machine Learning Engineer
•
Coding
•
medium
Implement Beam Search decoding for a language model given a function that returns the next-token probabilities.
#Search Algorithms
#Heuristics
#NLP
Machine Learning Engineer
•
Coding
•
medium
Implement a Token Bucket rate limiter for the OpenAI API. It needs to handle multiple users, support concurrent requests, and be highly performant.
#Concurrency
#System Design
#Data Structures
Machine Learning Engineer
•
Coding
•
hard
Write a PyTorch script to manually parallelize a simple feed-forward network across 2 GPUs using naive pipeline parallelism. Handle the forward and backward passes.
#PyTorch
#Distributed Computing
Machine Learning Engineer
•
Coding
•
medium
Given a Directed Acyclic Graph (DAG) representing a computation graph of ML operations, write an algorithm to schedule the operations on a fixed number of parallel workers to minimize total execution time.
#Graphs
#Scheduling
#Topological Sort
Machine Learning Engineer
•
Coding
•
hard
Implement a mock distributed parameter server. Write the worker code that computes gradients and the server code that aggregates them and updates weights, communicating via queues.
#Concurrency
#Distributed Systems
#Python
Machine Learning Engineer
•
Coding
•
hard
Implement the Aho-Corasick algorithm to efficiently search for a large dictionary of toxic words within a streaming text generation output.
#Trees
#Trie
#String Matching
Machine Learning Engineer
•
Coding
•
medium
Given a list of text highlight spans (start_index, end_index) from multiple human labelers, write a function to merge all overlapping spans into a consolidated list of highlighted regions.
#Arrays
#Sorting
Machine Learning Engineer
•
Coding
•
medium
Implement Top-K and Nucleus (Top-p) sampling given a tensor of logits. Ensure your implementation is numerically stable and efficient.
#Probability
#PyTorch
#Algorithms
Machine Learning Engineer
•
Coding
•
medium
Write a highly optimized self-attention mechanism in PyTorch from scratch. Include support for causal masking and explain the tensor shapes at each step.
#PyTorch
#Transformers
#Linear Algebra
Machine Learning Engineer
•
Coding
•
medium
Implement a simplified Byte Pair Encoding (BPE) tokenizer. Given a corpus of text and a target vocabulary size, write a function to find the most frequent adjacent pair of characters or tokens and merge them.
#Strings
#Hash Maps
#NLP
Machine Learning Engineer
•
Coding
•
hard
Implement Multi-Head Attention from scratch in PyTorch. Ensure it is batched and optimized for memory.
#PyTorch
#Transformers
#Linear Algebra
Machine Learning Engineer
•
Coding
•
medium
Write a Byte-Pair Encoding (BPE) tokenizer from scratch. Given a corpus of text and a target vocabulary size, implement the training and tokenization functions.
#String Manipulation
#Data Structures
#NLP
Machine Learning Engineer
•
Coding
•
hard
Implement a Ring All-Reduce algorithm simulation. Given an array of N nodes, each with an array of numbers, write code to perform the scatter-reduce and all-gather phases.
#Networking
#Parallel Computing
#Algorithms
Machine Learning Engineer
•
Coding
•
hard
Implement an autoregressive generation loop with KV Caching. Assume a simplified transformer block is provided.
#Memory Management
#Transformers
#PyTorch
Machine Learning Engineer
•
System Design
•
hard
Design the serving infrastructure for ChatGPT to handle millions of concurrent users. How do you manage state, batching, and latency?
#Distributed Systems
#Inference Scaling
#Continuous Batching
Machine Learning Engineer
•
System Design
•
medium
Design a distributed data pipeline to ingest, filter, and deduplicate 10 Petabytes of raw web scrape data for LLM pre-training.
#Big Data
#MinHash
#Deduplication
#Distributed Computing
Machine Learning Engineer
•
System Design
•
hard
Design the inference architecture for a ChatGPT-like service to handle millions of concurrent users with minimal Time-To-First-Token (TTFT) and high throughput.
#Inference
#Scalability
#Concurrency
#Continuous Batching
Machine Learning Engineer
•
System Design
•
hard
Design the training infrastructure and orchestration system for a Reinforcement Learning from Human Feedback (RLHF) pipeline.
#RLHF
#PPO
#Architecture
#Orchestration
Machine Learning Engineer
•
System Design
•
hard
Design a fault-tolerant cluster orchestration system for training a 100B+ parameter model across 10,000 GPUs that can survive frequent node failures.
#Infrastructure
#Fault Tolerance
#Kubernetes
Machine Learning Engineer
•
System Design
•
hard
Design a data pipeline to scrape, clean, deduplicate, and tokenize 10TB of raw web text data for LLM pretraining.
#Data Engineering
#MapReduce
#MinHash
Machine Learning Engineer
•
System Design
•
hard
Design an end-to-end RLHF pipeline. Walk me through the system architecture from human labeling interfaces to the final PPO training loop.
#RLHF
#Data Pipelines
#Model Training
Machine Learning Engineer
•
System Design
•
medium
Design a system to detect and filter PII (Personally Identifiable Information) from a massive, continuously updating stream of training data.
#Security
#Stream Processing
#NLP
Machine Learning Engineer
•
System Design
•
medium
Design an evaluation framework for the continuous deployment of new LLM checkpoints. How do you ensure a new model doesn't regress on coding tasks while improving on creative writing?
#MLOps
#Evaluation
#Testing
Machine Learning Engineer
•
System Design
•
hard
Design a multi-tenant vector database system to support embedding search for millions of users (e.g., for ChatGPT custom knowledge bases).
#Databases
#Information Retrieval
#Scalability
Machine Learning Engineer
•
System Design
•
hard
You are tasked with reducing the Time-To-First-Token (TTFT) and increasing the generation speed of an existing LLM API. Walk me through the specific optimizations you would implement.
#Inference Optimization
#Latency
#Hardware
Machine Learning Engineer
•
System Design
•
hard
How would you design a system to train a 100B+ parameter model across 10,000 GPUs? Detail the parallelism strategies you would use.
#Distributed Training
#3D Parallelism
#Network Topology
Machine Learning Engineer
•
Technical
•
medium
Explain the difference between Layer Normalization and RMSNorm. Why has the industry largely shifted to RMSNorm for LLMs?
#Deep Learning
#Optimization
Machine Learning Engineer
•
Technical
•
hard
Explain FlashAttention. How does it optimize memory bandwidth, and what are the trade-offs?
#CUDA
#Memory Bandwidth
#Hardware Optimization
Machine Learning Engineer
•
Technical
•
hard
Explain Rotary Positional Embeddings (RoPE). Why are they preferred over absolute positional embeddings in modern LLMs?
#Transformers
#Mathematics
#NLP
Machine Learning Engineer
•
Technical
•
medium
Explain the mathematical intuition behind Rotary Position Embeddings (RoPE) and why it is preferred over absolute positional embeddings in modern LLMs.
#Mathematics
#Transformers
#Architecture
Machine Learning Engineer
•
Technical
•
hard
During the distributed pre-training of a 70B parameter model, you observe sudden, unrecoverable loss spikes. Walk me through your step-by-step debugging process.
#Distributed Training
#Optimization
#Debugging
Machine Learning Engineer
•
Technical
•
easy
Explain the vanishing gradient problem. How do architectural innovations like Residual Connections (ResNets) and Transformers mitigate this issue?
#Deep Learning Basics
#Architecture
Machine Learning Engineer
•
Technical
•
medium
How do you handle catastrophic forgetting when fine-tuning a pre-trained LLM on a highly specific, narrow domain?
#Fine-tuning
#Transfer Learning
Machine Learning Engineer
•
Technical
•
medium
What are the specific trade-offs between Tensor Parallelism (TP), Pipeline Parallelism (PP), and Fully Sharded Data Parallelism (FSDP)? When would you use each?
#Model Parallelism
#GPU
#Networking
Machine Learning Engineer
•
Technical
•
medium
Derive the exact GPU memory requirements for training a 7 Billion parameter model using the Adam optimizer in mixed precision (fp16/bf16).
#Hardware
#Optimization
#Memory Management
Machine Learning Engineer
•
Technical
•
hard
Explain how FlashAttention works. Why does it reduce memory bandwidth, and how does it achieve exact attention mathematically?
#Transformers
#CUDA
#Hardware Optimization
Machine Learning Engineer
•
Technical
•
hard
What are the mathematical and practical differences between Proximal Policy Optimization (PPO) and Direct Preference Optimization (DPO) in the context of RLHF?
#Reinforcement Learning
#RLHF
#Loss Functions
Machine Learning Engineer
•
Technical
•
medium
What is the difference between Tensor Parallelism and Pipeline Parallelism? When would you use each, and what are their respective communication bottlenecks?
#Distributed Systems
#Parallel Computing
Product Manager
•
Behavioral
•
hard
Tell me about a time you had to launch a product with highly ambiguous or shifting regulatory constraints. How did you manage the risk?
#Regulatory Compliance
#Risk Management
#Ambiguity
Product Manager
•
Behavioral
•
medium
Describe a time you strongly disagreed with an engineering or research lead regarding a product feature. How did you resolve it?
#Conflict Resolution
#Cross-functional
#Influence
Product Manager
•
Behavioral
•
hard
OpenAI moves incredibly fast. Tell me about a time you had to pivot your entire product roadmap overnight due to a market shift or competitor launch.
#Adaptability
#Fast-paced
#Resilience
Product Manager
•
Behavioral
•
easy
Tell me about a product or feature you launched that completely failed. What was the root cause, and what did you learn?
#Learning
#Humility
#Post-mortem
Product Manager
•
Behavioral
•
hard
How do you manage external and internal stakeholders when a highly anticipated model release is delayed by months due to unforeseen safety alignment issues?
#Stakeholder Management
#Safety
#Communication
Product Manager
•
Behavioral
•
medium
Tell me about a time you disagreed with an engineering or research team on the readiness of a machine learning model for production.
#Stakeholder Management
#Conflict Resolution
#Model Evaluation
Product Manager
•
Behavioral
•
medium
Describe a time you had to pivot a product roadmap due to a sudden technological breakthrough or competitor launch.
#Roadmapping
#Agile
#Competitor Analysis
Product Manager
•
Behavioral
•
medium
A journalist reports that a customer is using the OpenAI API to generate deepfake political content at scale. How do you handle this crisis?
#Policy
#Abuse
#Crisis Management
Product Manager
•
Behavioral
•
medium
Tell me about a time you had to make a critical product decision with highly incomplete or contradictory data.
#Ambiguity
#Decision Making
#Risk Assessment
Product Manager
•
Behavioral
•
hard
Tell me about a time you had to balance product growth with safety or ethical considerations. How would you apply that to a potential jailbreak vulnerability in GPT-4?
#AI Safety
#Ethics
#Risk Management
Product Manager
•
System Design
•
medium
How would you improve the 'Memory' feature in ChatGPT to make it more useful without creeping users out?
#Personalization
#Privacy
#UX Design
Product Manager
•
System Design
•
medium
Design a new API product that makes it effortless for developers to implement Retrieval-Augmented Generation (RAG) without managing their own vector databases.
#RAG
#Developer Tools
#API Design
Product Manager
•
System Design
•
hard
A major healthcare provider wants to use our API but requires strict HIPAA compliance and zero data retention. How do you design the product architecture to support this?
#Privacy
#Compliance
#Enterprise Architecture
Product Manager
•
System Design
•
hard
Design the backend architecture for ChatGPT's real-time voice feature to ensure latency stays under 300ms.
#Real-time Streaming
#Latency
#Audio Processing
Product Manager
•
System Design
•
hard
Design a telemetry system to collect user feedback and usage patterns on enterprise model responses without violating strict Zero Data Retention (ZDR) agreements.
#Data Privacy
#Telemetry
#Enterprise Architecture
Product Manager
•
System Design
•
medium
You notice that API latency for GPT-4o has spiked by 200ms globally. Walk me through your debugging process as a PM.
#Debugging
#Infrastructure
#Latency
Product Manager
•
System Design
•
hard
Design a system to handle rate limiting for the OpenAI API across millions of developers with different tier limits.
#Distributed Systems
#API
#Scalability
Product Manager
•
System Design
•
medium
Design a product feature to help educators detect AI-generated essays. What are the technical limitations?
#Education
#Watermarking
#AI Detection
Product Manager
•
System Design
•
hard
Walk me through how you would design the infrastructure and user experience to support real-time, low-latency voice conversations in ChatGPT.
#Real-time Systems
#Latency Optimization
#UX/UI
Product Manager
•
System Design
•
hard
Design a rate-limiting and tiering system for the OpenAI API to handle sudden viral usage spikes while ensuring enterprise SLAs.
#Scalability
#API Design
#SLA Management
Product Manager
•
Technical
•
hard
We are experiencing a severe GPU shortage. How do you balance API rate limits between the free tier, pay-as-you-go developers, and massive enterprise clients?
#Compute Allocation
#Pricing
#Trade-offs
Product Manager
•
Technical
•
medium
How would you prioritize features for the next iteration of ChatGPT Enterprise?
#Prioritization
#B2B
#Enterprise SaaS
Product Manager
•
Technical
•
medium
What metrics would you use to measure the success of the Custom GPTs marketplace?
#Marketplace Dynamics
#Engagement Metrics
#Monetization
Product Manager
•
Technical
•
medium
Explain the trade-offs between fine-tuning a model versus using Retrieval-Augmented Generation (RAG) for an enterprise customer looking to build an internal knowledge bot.
#RAG
#Fine-tuning
#LLM Architecture
Product Manager
•
Technical
•
hard
How would you price a new multimodal API feature, such as Sora video generation, for developers?
#Pricing Strategy
#Compute Costs
#Developer Ecosystem
Product Manager
•
Technical
•
hard
How should OpenAI defend its competitive moat against rapidly improving open-source models like Llama 3?
#Competitive Strategy
#Open Source
#Ecosystem Building
Product Manager
•
Technical
•
medium
An enterprise customer complains that the API's latency has increased by 200ms over the last week. How do you investigate and resolve this?
#Root Cause Analysis
#API Performance
#Customer Success
Product Manager
•
Technical
•
medium
How would you improve the feedback loop from end-users in ChatGPT to better identify and reduce model hallucinations?
#User Experience
#Data Collection
#RLHF
Product Manager
•
Technical
•
hard
Evaluate the trade-offs of building a native search engine within ChatGPT versus partnering with an existing search provider (like Bing).
#Build vs Buy
#Strategic Partnerships
#Search Architecture
Product Manager
•
Technical
•
hard
Design a monetization and go-to-market strategy for Sora (OpenAI's video generation model).
#Monetization
#Generative Video
#Go-to-Market
Product Manager
•
Technical
•
hard
Should OpenAI build a dedicated search engine to compete directly with Google? Walk me through your strategic reasoning.
#Market Expansion
#Search
#Competitive Analysis
Product Manager
•
Technical
•
medium
How would you prioritize the roadmap for ChatGPT Enterprise versus the ChatGPT Consumer tier?
#B2B vs B2C
#Roadmapping
#Resource Allocation
Product Manager
•
Technical
•
medium
Data shows that Custom GPTs have a high creation rate but very low 7-day retention. How do you investigate and fix this?
#Retention
#User Engagement
#Root Cause Analysis
Product Manager
•
Technical
•
hard
Pitch a new input/output modality for the next major model release (e.g., GPT-5) beyond text, image, and audio.
#Multimodal AI
#Innovation
#Future Tech
Product Manager
•
Technical
•
hard
Evaluate the cannibalization risk of OpenAI releasing open-weights models (like Whisper) versus keeping everything behind a closed API.
#Open Source
#Moats
#Developer Ecosystem
Product Manager
•
Technical
•
hard
What do you believe is the biggest threat to OpenAI's competitive moat over the next 3 years, and how should we defend against it?
#Competitive Advantage
#AI Market
#Threat Analysis
Product Manager
•
Technical
•
medium
ChatGPT Daily Active Users (DAU) dropped by 15% week-over-week. Walk me through exactly how you would investigate this.
#Root Cause Analysis
#Analytics
#Metrics
Product Manager
•
Technical
•
hard
How do you quantitatively measure the 'helpfulness' of a new model release before pushing it to 100% of users?
#Model Evaluation
#RLHF
#A/B Testing
Product Manager
•
Technical
•
easy
Define the top 3 North Star metrics for the OpenAI API platform.
#API Platform
#B2B
#KPIs
Product Manager
•
Technical
•
medium
We are launching a new real-time voice mode for ChatGPT. What are your strict launch criteria?
#Launch Criteria
#Multimodal
#Quality Assurance
Product Manager
•
Technical
•
hard
How do you A/B test a new safety alignment prompt that reduces harmful outputs but might also increase false refusals (degrading user experience)?
#A/B Testing
#Alignment
#Trade-offs
Product Manager
•
Technical
•
medium
How do you measure the success of the GPT Store marketplace?
#Marketplaces
#Ecosystem
#KPIs
Product Manager
•
Technical
•
hard
You have a fixed, limited amount of GPU compute. How do you allocate it between training GPT-5, serving ChatGPT free users, and serving high-paying API customers?
#Resource Management
#Compute
#Prioritization
Product Manager
•
Technical
•
medium
What specific metrics would you use to evaluate a new code generation model intended to replace the current version of Codex?
#Code Generation
#Evaluation
#Developer Tools
Product Manager
•
Technical
•
hard
How do you track, measure, and reduce model hallucinations in a production environment where we don't know the ground truth of user queries?
#Hallucinations
#Trust
#Model Evaluation
Product Manager
•
Technical
•
medium
Explain how Transformer architecture works to a non-technical Fortune 500 CEO who is considering buying ChatGPT Enterprise.
#ML Architecture
#Communication
#Executive Presence
Product Manager
•
Technical
•
medium
A customer is deciding between fine-tuning a model and using Retrieval-Augmented Generation (RAG). How do you guide them? What are the technical trade-offs?
#LLM Optimization
#Architecture
#Customer Advisory
Product Manager
•
Technical
•
hard
How do you balance reducing bias in a model (e.g., ensuring diverse representation) while maintaining its ability to reflect historical facts accurately?
#Alignment
#Bias
#Ethics
Product Manager
•
Technical
•
hard
What is your framework for deciding when a model should outright refuse a user prompt versus providing a nuanced, safe answer?
#Policy
#UX
#Alignment
Product Manager
•
Technical
•
medium
A zero-day 'jailbreak' prompt goes viral on Twitter, allowing users to bypass all safety filters on GPT-4. Walk me through your immediate execution plan.
#Incident Response
#Security
#Agile
Software Engineer
•
Behavioral
•
medium
Tell me about a production outage you caused or resolved. What was the root cause and how did you prevent it from happening again?
#Incident Management
#Accountability
#Post-mortems
Software Engineer
•
Behavioral
•
medium
OpenAI moves very fast. Tell me about a time you had to navigate extreme ambiguity without clear requirements.
#Adaptability
#Ambiguity
#Initiative
Software Engineer
•
Behavioral
•
medium
Describe a situation where you had to work closely with researchers or non-engineers to deploy a complex system.
#Communication
#Cross-functional
#Empathy
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a trade-off between shipping quickly and ensuring system safety/reliability.
#Trade-offs
#Decision Making
#Safety
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to make a trade-off between shipping a feature quickly and ensuring the safety, security, or reliability of the system.
#Trade-offs
#Safety
#Decision Making
Software Engineer
•
Behavioral
•
medium
Describe a project where you had to balance engineering perfection with the need to get a product to market quickly.
#Trade-offs
#Product Sense
#Execution
Software Engineer
•
Behavioral
•
medium
How do you prioritize tasks when you have multiple urgent requests from different stakeholders, such as AI researchers needing infra support vs. PMs needing API features?
#Prioritization
#Communication
#Stakeholder Management
Software Engineer
•
Behavioral
•
medium
OpenAI moves incredibly fast. Tell me about a time you had to pivot your entire project due to changing requirements or new research breakthroughs.
#Agility
#Resilience
#Project Management
Software Engineer
•
Behavioral
•
medium
OpenAI often faces a tension between shipping fast and ensuring AI safety. Tell me about a time you had to make a trade-off between speed and safety/reliability.
#Trade-offs
#Safety
#Decision Making
Software Engineer
•
Behavioral
•
medium
OpenAI moves incredibly fast. Tell me about a time you had to learn a completely new technology or domain in a matter of days to deliver a project.
#Learning Agility
#Adaptability
#Drive
Software Engineer
•
Behavioral
•
medium
Tell me about a time you discovered a significant security or safety flaw in a system. What steps did you take?
#Security
#Integrity
#Problem Solving
Software Engineer
•
Behavioral
•
easy
Why OpenAI? How do your personal goals align with our mission to ensure Artificial General Intelligence benefits all of humanity?
#Motivation
#Mission Alignment
#Values
Software Engineer
•
Behavioral
•
medium
Describe a situation where you strongly disagreed with a technical decision made by your team. How did you handle it?
#Conflict Resolution
#Communication
#Leadership
Software Engineer
•
Behavioral
•
medium
OpenAI moves extremely fast and research breakthroughs can deprecate engineering work overnight. Describe a situation where you had to pivot your entire project architecture due to sudden requirement changes.
#Adaptability
#Resilience
#Agile
Software Engineer
•
Behavioral
•
medium
Tell me about a time you had to ship a critical feature under extreme time pressure and high ambiguity.
#Adaptability
#Execution
#Ambiguity
Software Engineer
•
Behavioral
•
medium
Describe a situation where you had to dive into a codebase in a language or framework you were completely unfamiliar with. How did you become productive?
#Learning
#Problem Solving
#Ambiguity
Software Engineer
•
Behavioral
•
easy
Why OpenAI? How does your personal mission align with our goal of ensuring Artificial General Intelligence (AGI) benefits all of humanity?
#Mission Alignment
#Ethics
#Motivation
Software Engineer
•
Behavioral
•
hard
Tell me about the most complex technical problem you've solved that had no existing literature or StackOverflow answers.
#Innovation
#First Principles
#Deep Technical Expertise
Software Engineer
•
Behavioral
•
easy
Why OpenAI? How do your personal values align with our mission to ensure Artificial General Intelligence (AGI) benefits all of humanity?
#Mission Alignment
#Motivation
#Ethics
Software Engineer
•
Behavioral
•
medium
Describe a production incident you caused or were involved in. What was the root cause and how did you fix it?
#Post-mortems
#Accountability
#System Reliability
Software Engineer
•
Behavioral
•
medium
Tell me about a time you disagreed with a senior engineer or researcher on a technical approach. How did you resolve it?
#Conflict Resolution
#Communication
#Ego
Software Engineer
•
Behavioral
•
easy
What excites you most about Artificial General Intelligence (AGI), and what concerns do you have about its deployment?
#Mission Alignment
#AI Safety
#Ethics
Software Engineer
•
Behavioral
•
medium
Tell me about a time you strongly disagreed with a technical decision made by your team. How did you handle it?
#Conflict Resolution
#Communication
#Technical Leadership
Software Engineer
•
Behavioral
•
easy
How do you prioritize tasks when faced with multiple urgent requests from different teams?
#Time Management
#Prioritization
#Communication
Software Engineer
•
Coding
•
medium
Design a thread-safe token bucket rate limiter for the OpenAI API.
#Multithreading
#Locks
#System Design Basics
Software Engineer
•
Coding
•
medium
Write an algorithm to efficiently merge multiple sorted streams of log data (timestamped events) from thousands of different GPU nodes into a single chronological stream.
#Heaps
#Sorting
#Distributed Data
Software Engineer
•
Coding
•
hard
Write a C++ program to efficiently manage memory pools for variable-length tensor allocations to avoid fragmentation.
#C++
#Memory Management
#Data Structures
Software Engineer
•
Coding
•
medium
Find the longest substring with at most K distinct characters. (Analogy: optimizing a context window for specific entity types).
#Sliding Window
#Strings
#Hash Maps
Software Engineer
•
Coding
•
hard
Implement a basic Byte-Pair Encoding (BPE) tokenizer from scratch given a corpus of text.
#Strings
#Data Structures
#NLP
Software Engineer
•
Coding
•
medium
Design a thread-safe rate limiter for the OpenAI API that can handle burst traffic and different tier limits (e.g., Free vs. Pro users).
#Concurrency
#System Design
#Data Structures
Software Engineer
•
Coding
•
medium
Write a Python async function to fetch data from multiple endpoints concurrently, with a strict timeout and exponential backoff retry logic.
#Python
#Asyncio
#Networking
Software Engineer
•
Coding
•
medium
Implement an LRU Cache with a Time-To-Live (TTL) feature. If an item is expired, it should not be returned.
#Data Structures
#Caching
Software Engineer
•
Coding
•
hard
Implement a concurrent web crawler to fetch web pages for building an LLM training dataset. The crawler must respect robots.txt, handle domain-level rate limits, and avoid memory overflow.
#Concurrency
#Graph Traversal
#System Resources
Software Engineer
•
Coding
•
easy
Given a stream of API request logs containing user_id, timestamp, and token_count, write a function to calculate the monthly billing per user based on a tiered pricing model.
#Data Processing
#Math
#Hash Maps
Software Engineer
•
Coding
•
medium
Implement a text justification algorithm optimized for streaming chunks of text as they are generated by an LLM, ensuring the UI updates smoothly without jarring reflows.
#String Manipulation
#Streaming Data
#UI/UX considerations
Software Engineer
•
Coding
•
medium
Merge K sorted streams of training data efficiently, assuming the streams are too large to fit into memory.
#Heaps
#External Sorting
#Pointers
Software Engineer
•
Coding
•
medium
Write an async Python script to fetch data from multiple endpoints, aggregate the results, and handle timeouts or partial failures gracefully.
#API Integration
#Asynchronous Programming
#Error Handling
Software Engineer
•
Coding
•
medium
Find the shortest path in a Directed Acyclic Graph (DAG) representing a neural network computation graph to optimize memory allocation.
#Graphs
#Topological Sort
#Dynamic Programming
Software Engineer
•
Coding
•
hard
Implement a sliding window attention mechanism algorithm that computes attention scores only for the last K tokens.
#Sliding Window
#Arrays
#Math
Software Engineer
•
Coding
•
hard
Implement a distributed task queue in Python using asyncio, supporting task priorities, retries with exponential backoff, and concurrency limits.
#Asynchronous Programming
#Heaps
#System Design
Software Engineer
•
Coding
•
medium
Write a function to perform matrix multiplication efficiently, then explain how you would optimize it for CPU cache locality.
#Math
#Memory Management
#Optimization
Software Engineer
•
Coding
•
medium
Given a list of API requests with start and end timestamps, find the maximum number of concurrent requests at any point in time.
#Arrays
#Sorting
#Sweep Line Algorithm
Software Engineer
•
Coding
•
hard
Write a streaming JSON parser that can handle incomplete JSON strings, similar to processing chunks generated sequentially by an LLM.
#Parsing
#State Machines
#String Manipulation
Software Engineer
•
Coding
•
medium
Design a thread-safe rate limiter using the Token Bucket algorithm to be used across a distributed API cluster.
#Concurrency
#Distributed Systems
#Data Structures
Software Engineer
•
Coding
•
hard
Implement a simplified version of Byte Pair Encoding (BPE) tokenization from scratch given a vocabulary and a text string.
#String Manipulation
#Greedy Algorithms
#Data Structures
Software Engineer
•
Coding
•
hard
Given a directed acyclic graph (DAG) representing dependencies of training jobs, write a function to execute them in the correct order concurrently.
#Graphs
#Topological Sort
#Concurrency
Software Engineer
•
Coding
•
medium
Merge K sorted arrays, representing log files from distributed training nodes, into a single sorted output.
#Heaps
#Sorting
#Distributed Systems
Software Engineer
•
Coding
•
medium
Design a data structure that supports insert, delete, and getRandom in O(1) time.
#Data Structures
#Hash Maps
#Arrays
Software Engineer
•
Coding
•
medium
Implement a Trie data structure for fast prefix matching to filter out blocked or policy-violating prompt keywords.
#Trees
#Strings
#Safety
Software Engineer
•
Coding
•
medium
Given a string of text, write a function to reverse the order of words, but keep the punctuation in its original relative position.
#Strings
#Two Pointers
Software Engineer
•
Coding
•
hard
Write a C++ program to efficiently multiply two large matrices, optimizing for CPU cache locality.
#C++
#Performance Optimization
#Computer Architecture
Software Engineer
•
Coding
•
medium
Implement a rate limiter for the OpenAI API that restricts users based on both requests per minute (RPM) and tokens per minute (TPM).
#Data Structures
#Concurrency
#API Design
Software Engineer
•
Coding
•
hard
Implement a distributed task queue for scheduling model evaluation jobs across a cluster of workers.
#Distributed Systems
#Concurrency
#Queues
Software Engineer
•
Coding
•
medium
Write a function to perform a simplified Byte-Pair Encoding (BPE) tokenization on a given string, given a vocabulary of base characters and a list of merge rules.
#String Manipulation
#Greedy Algorithms
#Hash Maps
Software Engineer
•
Coding
•
medium
Implement a function that takes a string and a list of forbidden words, and redacts the forbidden words in O(N) time.
#Trie
#Aho-Corasick
#String Matching
Software Engineer
•
Coding
•
medium
Merge K sorted streams of log data based on timestamps, where each stream is too large to fit in memory.
#Heaps
#Pointers
#External Sorting
Software Engineer
•
Coding
•
medium
Write a script to efficiently sample from a probability distribution of logits given a specific temperature parameter.
#Math
#Probability
#Arrays
Software Engineer
•
Coding
•
medium
Write an algorithm to find the longest common substring between two large text documents to detect potential training data memorization.
#Dynamic Programming
#Suffix Trees
#Rolling Hash
Software Engineer
•
Coding
•
hard
Given a Directed Acyclic Graph (DAG) representing a computational graph, write an executor that runs independent nodes in parallel.
#Graphs
#Topological Sort
#Multithreading
#Task Scheduling
Software Engineer
•
Coding
•
medium
Implement an LRU cache with a time-to-live (TTL) for each entry, ensuring expired items are evicted efficiently.
#Linked Lists
#Hash Maps
#Caching
Software Engineer
•
Coding
•
medium
Write a function to compute the self-attention matrix given Query, Key, and Value matrices, including the softmax step.
#Linear Algebra
#Matrix Multiplication
#Transformers
Software Engineer
•
Coding
•
hard
Implement a streaming JSON parser that yields valid JSON objects as chunks of characters arrive over a network.
#Parsing
#State Machines
#Streaming
Software Engineer
•
System Design
•
hard
Design the backend architecture for ChatGPT inference. How would you handle streaming responses, manage user context windows, and route requests to available GPU nodes?
#Distributed Systems
#Load Balancing
#WebSockets/SSE
#GPU Scheduling
Software Engineer
•
System Design
•
medium
Design a system to detect and block prompt injection attacks in real-time before they reach the core LLM.
#Security
#Stream Processing
#Classification
Software Engineer
•
System Design
•
hard
Design a multi-tenant architecture for fine-tuning models where enterprise users upload their own proprietary datasets.
#Multi-tenancy
#Security
#Data Isolation
#Job Queues
Software Engineer
•
System Design
•
hard
Design a system to handle web scraping at the scale of the entire internet for LLM training data collection.
#Distributed Crawling
#Deduplication
#Politeness Policies
Software Engineer
•
System Design
•
medium
Design a semantic caching layer for the OpenAI API to save compute on identical or highly similar prompts.
#Caching
#Embeddings
#Cost Optimization
Software Engineer
•
System Design
•
medium
Design a telemetry and alerting system to monitor GPU health and utilization across 10,000 nodes in real-time.
#Monitoring
#Time-Series Databases
#Data Aggregation
Software Engineer
•
System Design
•
hard
How would you design a system to load balance LLM inference requests across a heterogeneous GPU cluster (e.g., mixing A100s and H100s)?
#Load Balancing
#Hardware Awareness
#Scheduling
Software Engineer
•
System Design
•
hard
Design a scalable vector database for storing and querying billions of text embeddings.
#Vector Search
#HNSW
#Sharding
#Distributed Storage
Software Engineer
•
System Design
•
hard
Design a distributed, highly available rate-limiting system for the OpenAI API that handles millions of requests per second.
#Distributed Systems
#Redis
#Consistency
#API Gateways
Software Engineer
•
System Design
•
medium
Design a system to collect, store, and sample RLHF (Reinforcement Learning from Human Feedback) data at scale.
#Data Pipelines
#Databases
#Event Sourcing
Software Engineer
•
System Design
•
hard
Design the backend architecture for ChatGPT to support real-time streaming responses.
#Server-Sent Events (SSE)
#WebSockets
#Microservices
#Load Balancing
Software Engineer
•
System Design
•
medium
Design a system to handle webhooks for asynchronous API completions, ensuring at-least-once delivery.
#Webhooks
#Message Queues
#Reliability
Software Engineer
•
System Design
•
hard
Design a highly available distributed file system optimized for heavy, sequential read workloads during model training.
#File Systems
#Distributed Storage
#Throughput Optimization
Software Engineer
•
System Design
•
medium
Design a fine-tuning API where users can upload datasets and train custom models asynchronously.
#API Design
#Job Queues
#Storage
#Asynchronous Processing
Software Engineer
•
System Design
•
hard
Design an infrastructure to reliably serve large models (e.g., GPT-4) that require multiple GPU nodes for a single inference pass.
#Hardware Infrastructure
#Networking
#Model Serving
Software Engineer
•
System Design
•
hard
Design a system to monitor and detect model drift or harmful outputs in real-time across billions of API calls.
#Stream Processing
#Machine Learning
#Monitoring
Software Engineer
•
System Design
•
medium
Design a caching layer for LLM responses to minimize redundant compute for identical or semantically similar prompts.
#Caching
#Semantic Search
#System Architecture
Software Engineer
•
System Design
•
hard
Design a distributed data pipeline to ingest, clean, deduplicate, and tokenize petabytes of web text for LLM training.
#Big Data
#MapReduce
#Data Pipelines
#Storage
Software Engineer
•
System Design
•
hard
Design a rate-limiting system for the OpenAI API that handles millions of requests per second across different pricing tiers and token limits.
#Distributed Caching
#Redis
#Scalability
#Algorithms
Software Engineer
•
System Design
•
hard
Design the backend infrastructure for ChatGPT, focusing specifically on low-latency streaming of tokens back to the client.
#WebSockets
#Server-Sent Events
#Microservices
#Latency Optimization
Software Engineer
•
System Design
•
hard
Design a distributed file system for storing massive text datasets (petabytes) used for pre-training LLMs.
#Storage
#Distributed Systems
#High Throughput
Software Engineer
•
System Design
•
medium
Design an asynchronous batch processing system for OpenAI's Batch API, where users submit millions of prompts to be processed within 24 hours.
#Batch Processing
#Queues
#Cost Optimization
Software Engineer
•
System Design
•
medium
Design a system to monitor and detect toxic or policy-violating prompts in real-time with minimal latency impact on the main API.
#Security
#Machine Learning
#Stream Processing
Software Engineer
•
System Design
•
medium
Design a telemetry system to collect metrics and logs from millions of ChatGPT clients globally in real-time.
#Data Ingestion
#Streaming
#Analytics
Software Engineer
•
System Design
•
hard
Design a load balancer specifically for LLM inference nodes, considering that generation times vary wildly based on output length.
#Load Balancing
#Queueing Theory
#LLM Inference
Software Engineer
•
System Design
•
hard
Design a rate-limiting system for the OpenAI API that handles millions of requests per second globally.
#Distributed Systems
#Redis
#Scalability
Software Engineer
•
System Design
•
hard
Design a distributed key-value store optimized specifically for storing and retrieving LLM KV caches during inference.
#Distributed Systems
#Memory Management
#Latency Optimization
Software Engineer
•
System Design
•
hard
Design an infrastructure to reliably train a 100B+ parameter model across thousands of GPUs.
#Distributed Systems
#Machine Learning Infrastructure
#Fault Tolerance
Software Engineer
•
System Design
•
hard
Design the backend architecture for ChatGPT, focusing specifically on handling streaming responses and maintaining conversation history.
#WebSockets
#Server-Sent Events
#Databases
#State Management
Software Engineer
•
System Design
•
hard
Design a scalable Vector Database for storing and querying billions of embeddings with low latency.
#Databases
#Indexing
#Approximate Nearest Neighbor
#Distributed Systems
Software Engineer
•
System Design
•
hard
Design a vector database for semantic search and Retrieval-Augmented Generation (RAG).
#Databases
#Search
#Machine Learning
Software Engineer
•
System Design
•
hard
Design a telemetry and monitoring system for OpenAI's API that can handle millions of events per second and detect anomalies in latency or token generation rates in real-time.
#Stream Processing
#Data Pipelines
#Anomaly Detection
#Time-Series Databases
Software Engineer
•
System Design
•
hard
Design a system to handle distributed training checkpointing for a 100B+ parameter model. The system must ensure minimal downtime and data loss during frequent GPU node failures.
#Fault Tolerance
#Distributed Storage
#Network Bandwidth
#High Availability
Software Engineer
•
System Design
•
hard
Design a distributed key-value store optimized for storing and retrieving high-dimensional vector embeddings for a Retrieval-Augmented Generation (RAG) system.
#Vector Databases
#Sharding
#Replication
#Approximate Nearest Neighbor (ANN)
Software Engineer
•
Technical
•
medium
How would you profile and optimize a PyTorch training loop that is bottlenecked by data loading?
#Profiling
#I/O Optimization
#PyTorch
Software Engineer
•
Technical
•
hard
How does KV caching work in transformer inference, and how would you optimize its memory footprint?
#Transformers
#Memory Management
#Optimization
Software Engineer
•
Technical
•
hard
Explain how you would profile and optimize a PyTorch data loading pipeline that is currently bottlenecking GPU utilization during model training.
#PyTorch
#GPU Profiling
#I/O Optimization
#Multiprocessing
Software Engineer
•
Technical
•
hard
Describe the differences between Data Parallelism, Tensor Parallelism, and Pipeline Parallelism. When would you use each?
#Distributed Training
#Parallel Computing
#System Architecture
Software Engineer
•
Technical
•
medium
How would you debug a distributed training job where one GPU is consistently slower than the others (a straggler)?
#Debugging
#Distributed Systems
#Hardware
Software Engineer
•
Technical
•
medium
Explain the concept of gradient checkpointing (activation recomputation) and when you would use it.
#Memory Optimization
#Deep Learning
#Math
Software Engineer
•
Technical
•
hard
Describe how the Ring All-Reduce algorithm works in distributed deep learning.
#Distributed Algorithms
#Networking
#NCCL
Software Engineer
•
Technical
•
medium
How do you handle out-of-memory (OOM) errors in a production deep learning inference service?
#Production Engineering
#Memory Management
#Reliability
Software Engineer
•
Technical
•
hard
Explain how you would implement continuous batching (iteration-level scheduling) for LLM inference.
#Scheduling
#Inference
#Batching
Software Engineer
•
Technical
•
medium
What are the trade-offs of using FP16 vs BF16 vs INT8 for model inference?
#Quantization
#Numerical Precision
#Hardware
Software Engineer
•
Technical
•
hard
Explain Ring All-Reduce and its role in distributed deep learning.
#Distributed Systems
#Networking
#Algorithms
Software Engineer
•
Technical
•
hard
Explain how KV caching works during LLM inference. How would you optimize memory usage for it in a high-throughput environment?
#Transformers
#Memory Management
#Inference Optimization
Software Engineer
•
Technical
•
hard
How do you handle out-of-memory (OOM) errors during distributed training of a multi-billion parameter model?
#Distributed Training
#Memory Profiling
#PyTorch
Software Engineer
•
Technical
•
hard
How would you implement KV-cache management (e.g., PagedAttention) for batched LLM inference to maximize throughput and minimize memory fragmentation?
#Memory Management
#LLM Inference
#Hardware Architecture
Software Engineer
•
Technical
•
hard
Describe the differences between Data Parallelism, Tensor Parallelism, and Pipeline Parallelism.
#Distributed Training
#Deep Learning
#System Architecture
Software Engineer
•
Technical
•
medium
How does Python's Global Interpreter Lock (GIL) affect multithreaded data processing, and how would you bypass it for a heavy tokenization workload?
#Python
#Concurrency
#Performance
Software Engineer
•
Technical
•
hard
Explain how you would optimize a PyTorch training loop to minimize GPU memory fragmentation.
#PyTorch
#GPU
#Memory Management
Software Engineer
•
Technical
•
hard
How does CUDA memory management work, and what is the advantage of using pinned (page-locked) memory?
#CUDA
#C++
#Hardware Architecture
Software Engineer
•
Technical
•
medium
How would you profile and reduce the latency of a Python microservice serving a machine learning model?
#Python
#Profiling
#Microservices
Software Engineer
•
Technical
•
hard
Explain the concept of FlashAttention and why it is critical for scaling context windows in LLMs.
#Deep Learning
#Algorithm Optimization
#Hardware
Software Engineer
•
Technical
•
medium
How would you handle continuous deployment for a service where a bad deployment could cause a massive GPU cluster to idle, costing millions?
#CI/CD
#Risk Management
#Infrastructure
Software Engineer
•
Technical
•
medium
Explain the differences between Tensor Parallelism and Pipeline Parallelism. When would you use one over the other?
#Distributed Systems
#Parallel Computing
#Model Architecture
Software Engineer
•
Technical
•
medium
Explain how you would optimize a PyTorch data loader that is bottlenecking GPU utilization during training.
#PyTorch
#Performance Profiling
#Concurrency
Difficulty Radar
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Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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