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OpenAI practice

Software Engineer, Model Inference mock interview

Practice for a Software Engineer, Model Inference round at OpenAI. The AI interviewer asks out loud, follows up, and scores your answers after the session.

ML / AISeniorPythonC++CUDA
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What this interview will probe

This role builds and optimizes the systems that serve OpenAI's models in production, working alongside researchers to improve inference performance, throughput, and reliability for models powering ChatGPT and the API. Engineers introduce new techniques for low-latency, high-utilization serving of large transformers across GPU fleets. An interview would probe how inference differs from training (KV caching, batching/continuous batching, quantization), GPU memory and latency tradeoffs, and designing a serving stack that maximizes tokens-per-second under tight tail-latency constraints.

ExoForm is not affiliated with OpenAI. This is an independent practice page.

Stack

PythonC++CUDA

Related practice pages

FAQ

How should I prepare for a Software Engineer, Model Inference interview?

Read the role brief, refresh the core stack, and practice explaining tradeoffs out loud. Live interviews test clarity as much as knowledge.

What do I get after the interview?

ExoForm gives you an overall score, a verdict, competency scores, and answer-by-answer feedback.

Can I use my own job description instead?

Yes. You can paste any job description and run a custom interview instead of starting from the catalog.