Performance Engineer, Inference Systems mock interview

Что будет проверяться

This role optimizes the systems that serve Claude to millions of users, squeezing maximum throughput and minimum latency from large GPU clusters running frontier transformers. Work spans kernel-level optimization, batching and scheduling, and end-to-end profiling of the inference path. A technical interview would probe GPU performance fundamentals, the mechanics of LLM serving (KV cache management, speculative decoding, continuous batching), and how to find and fix the bottleneck limiting tokens-per-second in a production serving stack.

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