How do I approach ML System Design interview questions?

ML System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master ml system design interviews.

What difficulty level is this interview question?

This is a hard difficulty ML System Design question, commonly asked during Onsite rounds at Anthropic.

What role is this question designed for?

This question is commonly asked for Software Engineer candidates at Anthropic during technical interviews.

Design a batched inference API

Last updated: Apr 22, 2026

Quick Overview

This question evaluates competency in designing scalable, low-latency ML inference systems with dynamic batching, covering system architecture, request batching and scheduling, model routing/versioning, and operational concerns such as autoscaling, reliability, timeouts, and observability.

|Home/ML System Design/Anthropic

Design a batched inference API

Anthropic

Feb 8, 2026, 12:00 AM

hardSoftware EngineerOnsiteML System Design

Submit Your Answer to Earn 20XP

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Design a batched inference API

Last updated: Apr 22, 2026

Quick Overview

|Home/ML System Design/Anthropic

Design a batched inference API

Anthropic

Feb 8, 2026, 12:00 AM

hardSoftware EngineerOnsiteML System Design

Submit Your Answer to Earn 20XP

Loading comments...

Browse More Questions

More ML System Design•More Anthropic•More Software Engineer•Anthropic Software Engineer•Anthropic ML System Design•Software Engineer ML System Design

Your design canvas — auto-saved