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
Hard
Software Engineer Locked

Design a Distributed Crossword Solver

This question evaluates proficiency in constraint-solving algorithms and distributed system architecture, including data representation, efficient sea...

System Design
29
0
413 people solved
Apr 7, 2026
OpenAI logo
OpenAI
Hard
Data Scientist Locked

Compute churn with re-subscriptions

This question evaluates proficiency in event-time data manipulation, temporal aggregation, and subscription-state logic for computing conversion and r...

Data Manipulation (SQL/Python)
11
0
97 people solved
Jan 15, 2026
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Design reliable high-volume chatbot system

This question evaluates a candidate's ability to design scalable, highly available, and fault-tolerant backend architectures for stateful chatbot serv...

System Design
27
0
203 people solved
Dec 6, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Design webhook, POI, chat, CI/CD, payments

You are asked to design several large-scale backend systems in a single onsite session. The bar is breadth and judgment under time pressure: for each ...

System Design
21
0
335 people solved
Jul 4, 2025
OpenAI logo
OpenAI
Medium
Machine Learning Engineer Locked

Simulate Plant Infection Spread

This question evaluates graph traversal and grid-based simulation skills, including modeling a 2D grid as a graph, propagation dynamics with obstacles...

Coding & Algorithms
6
0
75 people solved
Apr 3, 2026
OpenAI logo
OpenAI
Medium
Machine Learning Engineer

Describe handling pressure and present your work

Describe handling pressure and present your work Behavioral Prompt: Delivering Under Severe Time Pressure You are interviewing for a technical role wh...

Behavioral & Leadership
14
0
171 people solved
Jul 27, 2025
OpenAI logo
OpenAI
Hard
Software Engineer

Design ChatGPT homepage with streaming choices

Design ChatGPT homepage with streaming choices System Design: ChatGPT‑Style Homepage with Streaming Goal Design a ChatGPT‑style web homepage end to en...

ML System Design
8
0
96 people solved
Jul 27, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design LLM search handling long token inputs

Design an LLM-powered search and question-answering system over a large corpus of documents such as internal wikis, PDFs, logs, contracts, and web pag...

ML System Design
17
0
169 people solved
Apr 6, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Implement toy-language types and generic substitution

Problem: Toy Language Type System (Printing + Generic Resolution) You are implementing a small type system for a custom “Toy Language”. Types can be: ...

Coding & Algorithms
71
1
1135 people solved
Nov 13, 2025
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Design a Retrieval-Augmented Generation (RAG) system

This question evaluates a candidate's ability to design production-grade Retrieval-Augmented Generation systems, testing competencies in information r...

ML System Design
6
0
101 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Design a payment processing system

This question evaluates system-design competency in building reliable payment workflows, covering distributed transaction handling, idempotent APIs, a...

System Design
33
0
362 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Design Slack-like messaging platform

Design a Slack-like team collaboration product. Core features: - Workspaces (tenants), users, and channels (public/private) - Direct messages (1:1 and...

System Design
12
0
94 people solved
Oct 31, 2025
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Design a URL Shortener

This question evaluates system design and distributed systems competencies, including scalability, availability, data modeling, API design, caching, s...

System Design
6
0
83 people solved
Jan 19, 2026
OpenAI logo
OpenAI
Medium
Data Scientist

Determine Metrics to Measure Free-Trial Impact on Subscriptions

Determine Metrics to Measure Free-Trial Impact on Subscriptions A/B Test: Free Trial Offer Impact on Subscription Behavior Scenario You are analyzing ...

Analytics & Experimentation
60
0
149 people solved
Aug 4, 2025
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Design Slack-like multi-tenant global messaging system

This question evaluates a candidate's ability to design large-scale, multi-tenant real-time messaging systems, testing competencies in distributed sys...

System Design
17
0
129 people solved
Dec 1, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Design a persistent key-value store

Design and implement an in-memory key-value store with a 'medium' layer that serializes the store to bytes for persistence. Provide four functions: se...

Coding & Algorithms
35
0
426 people solved
Sep 6, 2025
OpenAI logo
OpenAI
Hard
Software Engineer

Design a response-ranking ML system

Design a response-ranking ML system System Design: Ranking Candidate Text Responses to Maximize User Satisfaction You are designing an end-to-end mach...

ML System Design
8
0
87 people solved
Jul 28, 2025
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Implement Social Follow Recommendations

This question evaluates graph data structure design and traversal, set-based aggregation and ranking logic, and the ability to justify data structure ...

Coding & Algorithms
6
0
47 people solved
May 9, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Design a fullstack app with frontend focus

Design a fullstack app with frontend focus Design a Full‑Stack Web Application (Frontend Emphasis) Context You are given a 2–3 page requirements docum...

System Design
15
0
123 people solved
Jul 27, 2025
OpenAI logo
OpenAI
Medium
Data ScientistSenior+

Write SQL for post-trial conversion cohorts

Using the schema below, write SQL to compute, for users first exposed between 2025‑06‑01 and 2025‑06‑30 (inclusive), the intent‑to‑treat paid conversi...

Data Manipulation (SQL/Python)
1
0
14 people solved
Oct 13, 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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