OpenAI Interview Prep
OpenAI ML System Design Interview
How the ml system design round works at OpenAI: Design an ML-powered system: data, training, serving, evals.
Start a free OpenAI ml system design mockWhat this round tests
- Problem framing and metric selection
- Data and feature engineering
- Model choice and training
- Serving, monitoring, and evaluation
How to prepare for OpenAI's ml system design round
- Practice the ML design framework: clarify the goal → metrics → data → features → model → serving → monitoring.
- Be ready to discuss offline vs online metrics and tradeoffs.
- Study common systems: recommendations, ranking, fraud, search.
- Do mock ML design rounds and defend your choices.
Sample questions
Asked at OpenAI
- Design a retrieval-augmented question-answering system.
- Design an evaluation pipeline for an LLM feature.
More ml system design practice
- Design a recommendation system for a short-video feed.
- Design a fraud detection system for payments.
- Design search ranking for an e-commerce site.
FAQ
Does OpenAI have a ml system design round?
Yes. In the OpenAI loop this shows up as "ML / AI system design": Design an ML-powered system: data, training, serving, evals.
Is ML design only for ML engineers?
Primarily, but it also appears in some backend/infra roles touching ML systems. The depth expected scales with how ML-focused the role is.
How is ML design different from regular system design?
It adds the ML lifecycle on top of systems thinking: framing the objective, choosing metrics, engineering features, training, and — critically — serving and monitoring the model in production.
Ready to practice?
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Start a free OpenAI ml system design mock