Anthropic

AI safety and research company behind Claude, focusing on constitutional AI.

5 Rounds ~20 Days Very Hard

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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

All Roles Machine Learning Engineer 8

All Topics System Design 122 Algorithms 85 Culture Fit 63 SQL 27 Machine Learning 25 Leadership 25 Data Engineering 14 Security 12

Machine Learning Engineer • Coding • hard

Implement the forward pass of a Mixture of Experts (MoE) layer with a top-2 routing mechanism.

#MoE #PyTorch #Routing

Practice

Machine Learning Engineer • Coding • medium

Implement a multi-head self-attention mechanism from scratch in PyTorch, ensuring it is highly optimized for batch processing.

#PyTorch #Transformers #Linear Algebra

Practice

Machine Learning Engineer • Coding • hard

Write a function to perform Rotary Positional Embeddings (RoPE) on a given query and key tensor.

#PyTorch #Transformers #Positional Encodings

Practice

Machine Learning Engineer • Coding • hard

Implement a memory-efficient Ring Attention mechanism to handle extremely long context windows across multiple GPUs.

#Distributed Computing #Attention #Memory Optimization

Practice

Machine Learning Engineer • Coding • hard

Implement a multi-head self-attention mechanism from scratch in PyTorch. Ensure your implementation efficiently handles batched inputs and causal masking.

#PyTorch #Transformers #Attention Mechanism #Vectorization

Practice

Machine Learning Engineer • Coding • hard

Implement a custom PyTorch autograd function for a novel activation function, including both the forward and backward passes.

#PyTorch Internals #Calculus #Autograd

Practice

Machine Learning Engineer • Technical • medium

Explain the KV cache in transformer inference. How do techniques like PagedAttention or Ring Attention optimize it?

#Inference Optimization #Memory Management #Attention Mechanisms

Practice

Machine Learning Engineer • Technical • medium

What is the impact of mixed-precision training (e.g., BF16 vs FP16) on model convergence and memory? Why is BF16 generally preferred for LLMs?

#Numerical Precision #Hardware #Training Stability

Practice

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Senior Engineer

Focuses on core competencies, system constraints, and clear communication.

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Think Out Loud

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