OpenAI Interview Questions

OpenAI Interview Questions

Practice 274 real OpenAI interview questions for 2026 — real interview questions drawn from actual interviews with detailed solutions. OpenAI interview questions on this page span Coding & Algorithms, System Design, ML System Design, Machine Learning, and Data Manipulation (SQL/Python) and cover roles like Software Engineer, Machine Learning Engineer, Data Scientist, Android Engineer, and Frontend Engineer. For interview preparation expect a focus on production ML systems, scalable services, numerical correctness, experimental design, and communication: interviewers evaluate architecture decisions, tradeoffs, measurable impact, and the ability to ship robust systems under uncertainty. The loop runs stage-by-stage: a recruiter screen, a technical phone screen (coding or design), a virtual onsite with focused rounds (practical coding, system and ML design, model/debug deep dives, and behavioral/mission-fit), then team match and offer; typical timeline is about 4–8 weeks and difficulty is high. Practical coding leans toward real-world engineering problems rather than pure LeetCode puzzles. Software-engineer themes include consistent-hashing sharding, GPU job scheduling for text-to-video, payment systems with exactly-once semantics, and video orchestration. ML tracks emphasize resumable iterators and checkpoint/restore, streaming-entropy numerical stability, 1-NN implementations and debugging model backprop; data science focuses on churn, free-trial A/B tests, and SQL retention analysis. Use project deep-dives and worked examples when you prep.

274 Questions 1 Company08.01.2026
Showing 20 results
Role
OpenAI logo
OpenAI
Medium
Backend Engineer

Design a Real-Time Chess Service

Design an online chess service that supports real-time, two-player games. Users should be able to create or join a game, make legal moves, and see the...

System Design
18
0
212 people solved
Apr 22, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Explain Your Engineering Ownership

You are on an initial technical screening call for a Software Engineer role. Despite being an early-stage "recruiter" screen, it is unusually technica...

Behavioral & Leadership
10
0
134 people solved
Apr 4, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Build a Reliable Streaming Chat UI

You are building a React-based chat interface where assistant responses stream into the UI token by token in real time (the same UX as a typical LLM c...

Software Engineering Fundamentals
15
0
176 people solved
Apr 4, 2026
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Design a Payment Processing Service (Merchant to Payment Provider)

This system design question evaluates a candidate's ability to model a distributed payment processing service that coordinates authorization, capture,...

System Design
9
0
51 people solved
Jun 12, 2026
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Diagnose Transformer training and inference bugs

Debugging a Transformer That Intermittently Throws Shape/Dtype Errors and Fails to Converge You inherit a Transformer-based sequence model (decoder-on...

Machine Learning
104
0
816 people solved
Aug 11, 2025
OpenAI logo
OpenAI
Medium
Data ScientistSenior+

Debug and harden trial-assignment Python code

You are given the following simplified Python snippet used to assign users and trigger a 1‑month free trial: """ import random, datetime, requests def...

Data Manipulation (SQL/Python)
37
0
449 people solved
Oct 13, 2025
OpenAI logo
OpenAI
Hard
Data Scientist Locked

Assess free-month promotion impact

This question evaluates a data scientist's competency in experimental design, causal inference, metric definition and prioritization, bias identificat...

Analytics & Experimentation
14
0
216 people solved
Jan 22, 2026
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Infection Spread Simulation with Death Threshold

This question evaluates a candidate's ability to implement grid-based simulation with multi-state cellular automaton logic, testing practical applicat...

Coding & Algorithms
9
0
50 people solved
Jun 20, 2026
OpenAI logo
OpenAI
Medium
Software EngineerSenior+ Locked

Design a Real-Time Online Chess Platform

Design the backend for a globally distributed real-time chess platform supporting moves, spectators, clocks, reconnects, and failover. Define authorit...

System Design
1
0
14 people solved
May 23, 2026
OpenAI logo
OpenAI
Medium
Machine Learning Engineer

Implement Prefix Products and Their Backward Pass

Let x[0..n-1] be a sequence and define inclusive prefix products by y[i] = x[0] x[1] ... * x[i]. Work through the following variants. State how zero...

Machine Learning
3
0
39 people solved
Aug 23, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Debug a transformer training pipeline

Debug a Transformer training pipeline You are handed a PyTorch Transformer encoder–decoder training pipeline that misbehaves. The pipeline includes to...

Machine Learning
57
0
1000 people solved
Jul 31, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Implement an Extensible Chatbot App

Implement a ChatApp class that processes user messages and routes them to bot responders. The system must support multiple bot types, and the design m...

Software Engineering Fundamentals
22
0
347 people solved
Apr 26, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Debug a failing ML classifier

Debugging a Churn Prediction Pipeline With Poor Generalization Context You have inherited a binary churn prediction system. The goal is to predict whe...

Machine Learning
66
0
556 people solved
Jul 28, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design and optimize a RAG system

Scenario You are building a Retrieval-Augmented Generation (RAG) system for question answering over an internal document corpus (engineering wikis, de...

ML System Design
39
0
456 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Count Connected Friend Groups

Count Connected Friend Groups You are given an n x n symmetric adjacency matrix. is_connected[i][j] == 1 means person i and person j are directly conn...

Coding & Algorithms
6
0
42 people solved
Jul 1, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Design a multi-tenant CI/CD platform

Question Design a multi-tenant CI/CD system that runs pipelines triggered by Git activity, isolates tenants from one another, and scales to thousands ...

System Design
17
0
306 people solved
Sep 6, 2025
OpenAI logo
OpenAI
Hard
Software Engineer

Design IDE Sandbox and Payments

You are asked to discuss two system design prompts. For each one, define the users, functional requirements, non-functional requirements, APIs, core w...

System Design
8
0
82 people solved
Apr 7, 2026
OpenAI logo
OpenAI
Easy
Machine Learning Engineer Locked

How would you build an image classifier with dirty data?

This question evaluates a candidate's ability to design end-to-end image classification systems and manage noisy image datasets, testing competencies ...

ML System Design
48
0
472 people solved
Jan 6, 2026
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design a recommendation system end-to-end

Design a Recommendation System End-to-End You are asked to design a large-scale recommendation system that powers a personalized feed — for example, a...

ML System Design
20
0
213 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Medium
Machine Learning Engineer Locked

Design an OOD detection system

This question evaluates a candidate's competency in ML system design, specifically out-of-distribution detection, production monitoring, interpretabil...

ML System Design
19
0
158 people solved
Dec 14, 2025

Frequently Asked Questions

How difficult are OpenAI interview questions for software and ML roles in 2026?
OpenAI interviews in 2026 are challenging but not purely puzzle-driven: they reward practical engineering, systems thinking, and domain depth. Expect coding rounds that favor real-world tasks (reading and modifying components, debugging, performance-minded implementations) over contrived LeetCode riddles, plus heavy system and ML design for senior roles. Difficulty varies by track: Software Engineer interviews emphasize scalable distributed systems and orchestration; Machine Learning and Research tracks dig deeper into math, experiment design, and paper-level reasoning. Overall the loop is selective; prepare for multi-hour virtual onsites and high bar on correctness, clarity, and tradeoff justification.
What is the OpenAI interview process stage by stage and where do different question types appear?
The process typically starts with a recruiter or sourcer screen (30 minutes) covering fit and logistics, then a technical phone screen or hiring manager call that mixes coding and role-specific questions. Many loops include a paid or take-home exercise in applied roles, then a virtual onsite of four to six rounds: coding/debugging, system or ML systems design, a technical deep dive on your past work, and behavioral/mission-alignment conversations, followed by team-match interviews. Coding and Algorithms and Data Manipulation show up in early screens and onsite coding rounds; System Design and ML System Design dominate senior SWE and MLE rounds; Data Scientist rounds focus more on SQL, experiments, and A/B analysis.
How should I schedule my preparation and what timeline is realistic before interviewing at OpenAI?
Plan a 4–8 week preparation block aligned to the role. Weeks 1–2: solidify fundamentals—data structures, Python or chosen language fluency, and SQL skills with joins, windows, and CTEs. Weeks 3–4: practice role-specific system problems and ML fundamentals—distributed systems, caching, consistency, and experiment design. Weeks 5–6: run mock onsites, do timed coding, and prepare technical deep dives (projects, papers, metrics). Final 1–2 weeks: polish behavioral stories, team-fit pitch, and revisit tricky system/ML topics like checkpointing, numerical stability, and orchestration. Allow extra time if you must rebuild ML coding from scratch or reproduce papers.
What specific subtopics and problem types recur for OpenAI roles (coding, system design, ML, and data)?
For Software Engineers expect distributed-systems themes such as consistent hashing rings with virtual nodes, GPU job schedulers for text-to-video workloads, exactly-once payment processing, versioned social follow graphs, and video generation orchestration. Machine Learning Engineers see resumable iterators with checkpoint/restore, streaming entropy and numerical stability, 1-NN implementations and matrix gradient tricks, debugging MiniGPT-style training, mining novel images, and noisy-annotator strategies. Data Scientists focus on SQL for repeat churn, free-month promotion A/B tests, signup/retention lift calculations, and experiment measurement. Mobile and frontend roles weight architecture (MVVM, Compose) and model-usage quotas.
What are standout preparation tips and common pitfalls to avoid for OpenAI interviews?
Emphasize production-ready thinking: write clear, testable code, explain failure modes, and design for observability and reproducibility. For ML/research tracks, be ready to discuss papers, experimental design, statistical power, and how you'd debug and reproduce training runs. Avoid over-optimizing for abstract puzzle tactics; interviewers want debugging instincts, tradeoff reasoning, and a path to shipable systems. Common pitfalls include ignoring edge cases (concurrency, exactly-once semantics), skimming data-quality implications in experiments, failing to justify metric choices, and not framing past work in terms of tradeoffs and measurable impact during technical deep dives and team-match conversations.

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