# Inference batching system interview question Aced (formerly Exponent) publishes a public search API over its indexed pages; the guide is at https://www.aced.io/agents/agent-access. Source: https://www.aced.io/questions/5780/inference-batching-system Source observed: 2026-11-04T21:34:39.395Z Last checked: 2026-11-04T21:34:39.395+00:00 Indexed: 2026-11-05T01:52:39.665+00:00 --- # Design an inference batching system for a single GPU We provide this interview-practice question for designing an inference batching system that handles **up to 100 inputs per batch** while users wait synchronously. The goal is to maximize GPU utilization under compute constraints. The question asks: - How would you batch and process inputs? - How would you return responses to users? - What are the trade-offs? - What are the points of failure? - How would the design scale? ## Question details - **Reported interviews:** 9 - **Last asked:** 4 months ago - **Roles:** [Software Engineer](https://www.aced.io/questions?role=swe), [AI Engineer](https://www.aced.io/questions?role=ai-engineer), [Product Manager](https://www.aced.io/questions?role=pm), [Engineering Manager](https://www.aced.io/questions?role=em), [Machine Learning Engineer](https://www.aced.io/questions?role=ml-engineer), [Hardware Engineer](https://www.aced.io/questions?role=hardware-engineer) - **Companies:** [Anthropic](https://www.aced.io/questions?company=anthropic), [Nebius](https://www.aced.io/questions?company=nebius) - **Categories:** Artificial Intelligence, Machine Learning, System Design ## Interview experiences Five shared interview experiences are associated with this question. ### Nebius — Product Manager, Senior / L5 A candidate reported a good recruiter round. In the second product-case round with the hiring manager, the candidate was asked deep technical questions about AI. [Read the experience](https://www.aced.io/experiences/nebius-senior-product-manager-interview-fa03ff). ### Anthropic — Engineering Manager A candidate described formulaic interviews. For management questions, interviewers began with the largest organization the candidate had managed and continued with questions about that organization. The candidate noted that a bank organization had limited parallels, and would have preferred to introduce a smaller, more comparable organization earlier. [Read the experience](https://www.aced.io/experiences/anthropic-engineering-manager-interview-170078). ### Anthropic — Software Engineer, Staff / L6 A candidate described a 15-minute recruiter call, a phone design round, and a five-round onsite covering system design, coding, project deep dive, behavioral, and culture. The candidate found the process efficient and the bar high. AI-oriented technical questions were described as ordinary infrastructure questions when abstracted appropriately. The coding round was a practical project exercise rather than a multithreaded coding problem. The candidate was ultimately rejected without feedback. [Read the experience](https://www.aced.io/experiences/anthropic-staff-software-engineer-interview-6ecf1d). ### Anthropic — Software Engineer, Staff / L6 A candidate described a recruiter screen, coding phone screen, and virtual onsite consisting of coding, system design, hiring manager, culture, and a technical presentation rounds. Hiring paused before a different recruiter resumed the process. The candidate felt the system design round was the weakest part and did not receive an offer. [Read the experience](https://www.aced.io/experiences/anthropic-staff-software-engineer-interview-9bfb57). ### Anthropic — Software Engineer, Staff / L6 A candidate described an infrastructure software engineering process with a recruiter screen, live coding phone screen, and onsite loops covering system design, coding, culture, experiences and goals, and a technical project deep dive. The candidate said the questions were tied to GPU infrastructure and Anthropic's safety culture, and felt strongest in the project deep dive and weakest in a later coding round. [Read the experience](https://www.aced.io/experiences/anthropic-staff-software-engineer-interview-307d62). ## Community answers No answers have been contributed by the community yet. ## Related question - [Design a peer-to-peer file distribution system that spreads a 10GB file from a single bandwidth-constrained source to thousands of interconnected hosts, each with limited input/output bandwidth, un...](https://www.aced.io/questions/5781/design-p2p-file-distribution-system) ## Related courses ### [AI Engineering Interview Prep](https://www.aced.io/courses/ai-engineering) ![AI Engineering Interview Prep](https://images.ctfassets.net/x78yjrjc11pq/25mhKSvDOiCwC89lDj89Ah/9a5fbfacc8d93f05c238ab55baa4e5e5/fde.png?w=800&h=800&fm=webp&q=75) We cover AI engineering interviews at companies such as Google, Anthropic, Meta, and OpenAI through frameworks, example questions, mock interviews with senior engineers, system design, AI/ML concepts, AI-assisted coding, and behavioral rounds. ### [Generative AI Interviews](https://www.aced.io/courses/gen-ai-interviews) ![Generative AI Interviews](https://images.ctfassets.net/x78yjrjc11pq/BLBU7an1PjT0Mt2ZzAfDa/60e119c8bff0cfb8281dcb497177f6e3/AdobeStock_1510292201-min.jpeg?w=800&h=800&fm=webp&q=75) We help candidates prepare for interviews at AI-first and AI-powered companies. 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