Design a Dynamically Batched Inference API

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Design a high-concurrency language-model inference API that dynamically batches compatible requests on a limited GPU pool. Balance interactive latency and throughput through admission control, memory-aware scheduling, continuous batching, cancellation, streaming, fairness, and overload handling.

Design a Dynamically Batched Inference API

Company: Anthropic

Role: Machine Learning Engineer

Category: System Design

Difficulty: hard

Interview Round: Onsite

Overview: Design a high-concurrency language-model inference API that dynamically batches compatible requests on a limited GPU pool. Balance interactive latency and throughput through admission control, memory-aware scheduling, continuous batching, cancellation, streaming, fairness, and overload handling.

Read the full Anthropic Machine Learning Engineer interview experience this question came from

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Anthropic
Jul 8, 2026
hardMachine Learning EngineerOnsiteSystem Design
71
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