Anthropic ML System Design Interview Questions
Practice the exact questions companies are asking right now.
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Estimate VRAM and compare model parallelism
You are reasoning about GPU memory and parallelism for a transformer-like workload dominated by matrix multiplications. Part 1: Can one matmul’s tenso...
Design a low-latency ML inference API
System Design: Low‑Latency ML Inference API (Real‑Time) Context You are designing an in‑region, synchronous inference API used by product surfaces (e....
Design an LLM-based binary classifier
Design a Binary Text Classifier Using Only a Log-Probability Scoring Helper Context You are building a binary text classifier without fine-tuning. You...
Design a batch inference API
System Design: Async Inference Service API (POST Job, Poll for Results) Context You are designing an asynchronous inference service where clients subm...
Design a GPU inference API
System Design: GPU-Backed Multi-Model Inference API Context Design a production-grade inference platform for serving multiple ML models (e.g., LLMs, v...
Design an inference routing and scheduling layer
System Design: Routing Layer for Heterogeneous Inference Backends (GPU/CPU) Context You are asked to design a routing layer that sits between a user-f...
Review an inference API design for scale
System Design Review: Machine-Learning Inference API (Distributed Systems Focus) Background You are reviewing a teammate’s design document for a produ...
Design a prompt processing backend
System Design: Background Processing Backend for LLM Prompts Context Design a multi-tenant backend that processes large language model (LLM) prompts a...
Design a high-concurrency LLM inference service
You are designing an LLM inference platform that serves interactive user requests (chat/completions) on GPUs. Goals - Support high concurrency with pr...