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
Machine Learning Engineer
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Coding
•
medium
Implement a distributed all-reduce operation using a ring topology. You can write pseudo-code assuming basic send() and recv() primitives.
#Networking
#All-reduce
#Algorithms
#Parallel Computing
Machine Learning Engineer
•
System Design
•
hard
Design a fault-tolerant checkpointing system for a massive training run that minimizes GPU idle time during saves.
#Checkpointing
#I/O Optimization
#Fault Tolerance
Machine Learning Engineer
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Technical
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hard
Derive the memory requirements for training a 70B parameter model in mixed precision using AdamW and ZeRO-3 optimization.
#Distributed Training
#DeepSpeed
#Memory Profiling
Machine Learning Engineer
•
Technical
•
medium
Explain the difference between Tensor Parallelism (e.g., Megatron-LM) and Pipeline Parallelism. When would you use each?
#Tensor Parallelism
#Pipeline Parallelism
#Model Scaling
Machine Learning Engineer
•
Technical
•
medium
How do you handle straggler nodes or hardware failures in synchronous distributed training of large language models?
#Fault Tolerance
#Distributed Training
#Infrastructure
Machine Learning Engineer
•
Technical
•
hard
What are the specific trade-offs between Tensor Parallelism, Pipeline Parallelism, and Fully Sharded Data Parallel (FSDP)?
#Distributed Training
#Parallelism
#GPU Memory
Difficulty Radar
Based on recent AI-sourced data.
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The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.