Anthropic
AI safety and research company behind Claude, focusing on constitutional AI.
5 Rounds
~20 Days
Very Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
•
Coding
•
hard
Given a dataset of prompt-response pairs with boolean safety violation flags from human annotators and a classifier's probability scores, write a script to compute the ROC-AUC score from scratch.
#Python
#ML Metrics
#Algorithms
Data Scientist
•
Technical
•
hard
How would you design a robust evaluation metric to measure hallucination rates in Claude's summarization tasks across different domains (e.g., legal, medical, casual)?
#LLM Evaluation
#Hallucination
#Metrics Design
Data Scientist
•
Technical
•
hard
From a data distribution and statistical perspective, explain the differences between preparing preference data for Direct Preference Optimization (DPO) versus traditional RLHF (PPO).
#RLHF
#DPO
#Preference Data
Data Scientist
•
Technical
•
hard
How do you detect and mitigate data contamination (test set leakage) in the massive pre-training corpus of a large language model to ensure our benchmark scores are valid?
#Data Contamination
#Test Leakage
#Pre-training Data
Data Scientist
•
Technical
•
medium
Explain how you would cluster millions of unstructured user prompts to identify emerging use cases and feature requests.
#Unsupervised Learning
#NLP
#Clustering
Data Scientist
•
Technical
•
hard
Explain the difference between PPO (Proximal Policy Optimization) and DPO (Direct Preference Optimization) from a data requirements and modeling perspective.
#RLHF
#DPO
#PPO
Data Scientist
•
Technical
•
medium
How would you evaluate the coding capabilities of an LLM beyond just exact-match pass@k on standard datasets like HumanEval?
#Evaluation
#Code Generation
#Metrics
Data Scientist
•
Technical
•
hard
How would you design an evaluation metric to quantify the rate of subtle hallucinations in Claude's long-form summarization tasks?
#LLM Evaluation
#NLP
#Metrics Design
Data Scientist
•
Technical
•
hard
How would you measure the trade-off between helpfulness and harmlessness (the 'HHH' alignment) when evaluating a new model checkpoint?
#AI Safety
#Trade-off Analysis
#Experimentation
Data Scientist
•
Technical
•
medium
How would you detect and quantify data contamination (test set leakage) in our pre-training corpus?
#Data Processing
#NLP
#Model Evaluation
Data Scientist
•
Technical
•
hard
Explain the mathematics and intuition behind Proximal Policy Optimization (PPO) at a high level, and why it is preferred for RLHF.
#Reinforcement Learning
#Math
#RLHF
Data Scientist
•
Technical
•
medium
How do you handle severe class imbalance when training a classifier to detect rare jailbreak attempts in user prompts?
#Classification
#Imbalanced Data
#Security
Data Scientist
•
Technical
•
hard
What are the primary limitations and biases of using strong LLMs as judges for evaluating the outputs of other LLMs?
#LLM Evaluation
#Bias
#Research Methodology
Data Scientist
•
Technical
•
hard
Describe how you would detect data contamination (test set leakage) in a massive 5-trillion token pre-training corpus.
#Data Quality
#NLP
#Algorithms
Data Scientist
•
Technical
•
medium
Explain the concept of Constitutional AI. How would you quantitatively measure if a model is adhering to its constitution?
#Constitutional AI
#Alignment
#Metrics
Data Scientist
•
Technical
•
medium
What are the trade-offs between using automated LLM-as-a-judge evaluations versus human annotators for scoring model helpfulness?
#LLM Evaluation
#Bias
#Data Quality
Data Scientist
•
Technical
•
hard
How do you mitigate the 'length bias' (where models or humans prefer longer answers regardless of quality) in RLHF data?
#RLHF
#Bias Mitigation
#Modeling
Machine Learning Engineer
•
Coding
•
medium
Write a Python function to sample from a logits distribution using top-k and top-p (nucleus) sampling.
#Sampling
#Probability
#PyTorch
Machine Learning Engineer
•
Technical
•
hard
What is the Gumbel-Softmax trick, and in what scenarios would you use it in language modeling or reinforcement learning?
#Generative Models
#Reparameterization
#Math
Machine Learning Engineer
•
Technical
•
hard
Explain the mathematical formulation of RLHF (Reinforcement Learning from Human Feedback). Specifically, how does the PPO objective function work, and what are the common failure modes when fine-tuning a large language model?
#RLHF
#PPO
#Model Alignment
#Optimization
Machine Learning Engineer
•
Technical
•
medium
Explain the differences between Rotary Positional Embeddings (RoPE), ALiBi, and absolute positional embeddings. Why are relative positional embeddings preferred in modern LLMs?
#Transformers
#Positional Encoding
#LLM Architecture
Machine Learning Engineer
•
Technical
•
hard
What is Direct Preference Optimization (DPO) and how does it compare mathematically and practically to PPO?
#DPO
#RLHF
#Loss Functions
Software Engineer
•
Coding
•
hard
Implement a basic version of the scaled dot-product attention mechanism using pure NumPy. Include an optional causal mask.
#Linear Algebra
#NumPy
#Transformers
Software Engineer
•
Technical
•
hard
How would you optimize PyTorch dataloaders for training a model on a massive, multi-terabyte text dataset stored in AWS S3?
#PyTorch
#Data Pipelines
#Cloud Storage
#Performance Optimization
Software Engineer
•
Technical
•
hard
Explain how Key-Value (KV) caching works during transformer inference. Why is it necessary, and what are the memory implications for long context windows?
#Transformers
#Inference
#Memory Management
#LLM Architecture
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
SimulateUnwritten Rules
Think Out Loud
Always explain your thought process before writing code or drawing architecture.