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 14 results
Role
OpenAI logo
OpenAI
Medium
Machine Learning Engineer Locked

Design an Editable Text Buffer

This question evaluates data structure design, mutable state management, undo/redo semantics, and prefix-based autocomplete indexing with dynamic freq...

Coding & Algorithms
22
0
168 people solved
Mar 11, 2026
OpenAI logo
OpenAI
Hard
Software Engineer Locked

Implement follow graph with snapshots

This question evaluates a candidate's ability to design efficient persistent data structures and versioned state management for time-travel queries in...

Coding & Algorithms
27
1
204 people solved
Mar 1, 2026
OpenAI logo
OpenAI
Hard
Software Engineer

Implement a Contiguous Memory Allocator with Primitive Lists

Implement a Contiguous Memory Allocator with Primitive Lists Simulate an allocator over the contiguous address range [0, capacity), initially one free...

Coding & Algorithms
0
0
12 people solved
Feb 19, 2026
OpenAI logo
OpenAI
Easy
Software Engineer Locked

Simulate a Turn-Based Two-Player Game

This question evaluates API design, state management, move validation, board representation, and correctness guarantees for a turn-based game simulato...

Coding & Algorithms
11
0
77 people solved
Feb 13, 2026
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OpenAI
Hard
Software Engineer Locked

Implement type AST and infer generics

This question evaluates a candidate's ability to design an abstract syntax tree representation and implement generic type inference for a small langua...

Coding & Algorithms
26
2
363 people solved
Feb 11, 2026
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Implement an IPv4 Range Iterator

This question evaluates implementing iterative data structures and range-handling algorithms alongside numeric representation of IPv4 addresses and bi...

Coding & Algorithms
4
0
70 people solved
Jan 29, 2026
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OpenAI
Medium
Software Engineer Locked

Implement an IPv4 Iterator

This question evaluates proficiency in IPv4 address representation and arithmetic, CIDR parsing, iterator API design for forward and backward traversa...

Coding & Algorithms
4
0
47 people solved
Jan 19, 2026
OpenAI logo
OpenAI
Medium
Software Engineer

Implement delimiter-free string codec

Design an encoder/decoder for a list of strings. - Implement two functions: - encode(strings: List[str]) -> str - decode(blob: str) -> List[str] -...

Coding & Algorithms
13
0
110 people solved
Oct 31, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Implement compile-time function type verification

Implement a C++20 compile-time utility to verify whether a callable matches a target function type. Requirements: create a primary template is_callabl...

Coding & Algorithms
11
0
211 people solved
Sep 6, 2025
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OpenAI
Medium
Software Engineer

Implement expiring credit ledger

Implement an expiring-credit ledger that supports out-of-order events. Expose three functions with the following semantics: - add_credit(id, amount, t...

Coding & Algorithms
25
0
250 people solved
Sep 6, 2025
OpenAI logo
OpenAI
Medium
Machine Learning Engineer

Find earliest supporting version under constraints

You are given version strings formatted as {major}.{minor}.{patch}, e.g., "103.003.03". Each version either supports a feature or not. You may call is...

Coding & Algorithms
29
0
472 people solved
Sep 6, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Merge overlapping time intervals efficiently

Given a list of closed intervals [start, end] with 0 <= start <= end, merge all intervals that overlap or touch and return a minimal set of non-overla...

Coding & Algorithms
15
1
204 people solved
Jul 31, 2025
OpenAI logo
OpenAI
Hard
Machine Learning Engineer

Implement in-memory database insert and delete operations

Design and implement a simple in-memory database (key-value store) that supports the following operations: - insert(key, value): Insert a key-value pa...

Coding & Algorithms
12
0
170 people solved
Apr 6, 2025
OpenAI logo
OpenAI
Medium
Software Engineer Locked

Implement IPv4 and CIDR iterators

This question evaluates understanding of IPv4 addressing and CIDR notation, along with competency in binary/bitwise arithmetic, iterator construction,...

Coding & Algorithms
12
0
128 people solved
Jan 10, 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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