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
Software Engineer

Implement IPv4 iterators and CIDR expansion

Problem: IPv4 Iterators and CIDR Expansion You are implementing utilities to iterate over IPv4 addresses. An IPv4 address is in dotted-decimal form: A...

Coding & Algorithms
140
0
1015 people solved
Nov 15, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design a regional surge pricing strategy

Scenario You operate a ride-hailing platform. You need to design a system that sets surge multipliers (dynamic pricing) for a given region. Task Desig...

System Design
36
0
256 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design a search query autocomplete system

Question Design a search autocomplete system that suggests completions as the user types. Requirements - Sub-100ms latency per keystroke. - Suggestion...

System Design
22
0
252 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design a harmful video content moderation system

Question Design an end-to-end system to detect and moderate harmful videos on a large platform. Requirements - Detect multiple policy categories (viol...

ML System Design
8
0
162 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Hard
Software Engineer

Design an in-memory key-value database

Design an in-memory key-value database Design an In-Memory Key–Value Database (Technical Screen) Context Build an in-memory key–value (KV) database th...

System Design
37
0
287 people solved
Jul 31, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer Locked

Schedule Incremental Labeling Tasks

This question evaluates skills in designing stateful incremental schedulers, fairness and load-balancing algorithms, deterministic tie-breaking, and e...

Coding & Algorithms
12
0
115 people solved
Apr 8, 2026
OpenAI logo
OpenAI
Medium
Machine Learning Engineer

Implement vectorized NumPy ops and explain broadcasting

Implement vectorized NumPy code for: (a) computing pairwise cosine similarity between two real-valued matrices X (shape n×d) and Y (shape m×d) without...

Data Manipulation (SQL/Python)
22
0
320 people solved
Aug 11, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Explain motivation and mission alignment

In a behavioral interview for a mission-driven tech company, you are asked two related questions: 1. Why do you want to join this company? 2. How do...

Behavioral & Leadership
33
0
255 people solved
Oct 20, 2025
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OpenAI
Medium
Software Engineer

Implement a memory allocator with malloc/free

Problem You are implementing a simplified memory allocator over a contiguous memory region. Initialize the allocator with a fixed total size: - alloca...

Coding & Algorithms
18
0
199 people solved
Jan 9, 2026
OpenAI logo
OpenAI
Medium
Software Engineer

Generate Data Labeling Schedules

A data labeling platform manages tasks, AI models, and human annotators. Each entity has a 1-indexed string ID. You are given four integers: totalTask...

Coding & Algorithms
7
0
54 people solved
Apr 28, 2026
OpenAI logo
OpenAI
Medium
Software Engineer

Discuss views on AI safety and its impacts

You are interviewing for an AI-focused company. The interviewer spends most of the behavioral interview asking about your views on AI safety and its b...

Behavioral & Leadership
26
0
283 people solved
Dec 1, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design an image/video near-duplicate detection system

Question Design a system to detect near-duplicate images/videos (e.g., reuploads, minor edits, different encodes) at large scale. Requirements - Suppo...

ML System Design
11
0
154 people solved
Dec 15, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design enterprise RAG search system

Design enterprise RAG search system Design an End-to-End Enterprise RAG Search System Background You are tasked with designing a Retrieval-Augmented G...

ML System Design
12
0
175 people solved
Aug 4, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Build and troubleshoot image classification and backprop

Build and troubleshoot image classification and backprop CIFAR-like Noisy Dataset: Baseline, Data Quality Plan, and First-Principles Backprop Context:...

Machine Learning
75
0
570 people solved
Jul 27, 2025
OpenAI logo
OpenAI
Hard
Software Engineer

Design an in-memory database

Design an in-memory database System Design: In-Memory Database Engine (Single-Node Core, Scale-Out Aware) Context Design the core of an in-memory, sin...

System Design
31
0
381 people solved
Aug 4, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Design an ML search system

Design an ML‑Powered Enterprise Document Search System Context You are designing a multi‑tenant enterprise search system that indexes documents from m...

ML System Design
9
0
127 people solved
Sep 6, 2025
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Design a ChatGPT-like web chat UI

This English summary evaluates a question that assesses front-end–focused system design competencies such as UI architecture, real-time streaming inte...

System Design
35
0
273 people solved
Jan 2, 2026
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Implement a Contiguous Memory Manager

This question evaluates competence in designing efficient data structures and algorithms for interval management, contiguous allocation and deallocati...

Coding & Algorithms
10
0
149 people solved
Jan 19, 2026
OpenAI logo
OpenAI
Hard
Software EngineerSenior+ Locked

Design a Slack-like real-time messaging system

This question evaluates a candidate's competency in designing scalable, fault-tolerant real-time messaging systems, including message persistence and ...

System Design
57
0
406 people solved
Feb 12, 2026
OpenAI logo
OpenAI
Medium
Machine Learning Engineer Locked

Simulate Grid Infection

This question evaluates skills in multi-source breadth-first search, synchronous simulation updates, boundary handling, and off-by-one correctness wit...

Coding & Algorithms
20
0
134 people solved
Mar 9, 2026

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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