OpenAI Coding & Algorithms Interview Questions

Preparing for OpenAI Coding & Algorithms interview questions requires recognizing that OpenAI blends classic algorithmic rigor with product- and safety-oriented thinking. Interviews test algorithmic problem solving, data structures, time/space trade-offs, clean testable code, and the ability to reason about scaling, failure modes, and abuse vectors for real systems. Expect a multi-stage process—recruiter screen, one or two technical screens (pair coding or timed coding), and a final loop of 4–6 interviews covering coding, system design, deep-dives, and behavioral questions—lasting a few hours over one or two days. For interview preparation, practice medium-to-hard coding problems, timed pair-coding, system design scenarios relevant to model serving and data pipelines, and prepare concise STAR examples that highlight ownership and collaboration. Read OpenAI’s public materials and be ready to discuss trade-offs, testing, and safety considerations. Emphasize clear communication, test coverage, and justifying design choices; interviewers value well-reasoned, production-minded answers over trick solutions. Bring specific examples of shipping code and measurable impact.

90 Questions 1 Company08.01.2026
Showing 20 results
Role
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OpenAI
Medium
Software Engineer

Implement a GPU credit manager

Implement a GPU credit manager for a compute cluster. Each user has a nonnegative credit balance that can be increased (grantCredits(user, amount)), c...

Coding & Algorithms
23
0
280 people solved
Aug 8, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Implement an expiring GPU credits ledger

Implement an expiring GPU credits ledger for multiple users with three operations: 1) add_credit(user_id, amount, expiry_time): add a lot of credits t...

Coding & Algorithms
51
0
424 people solved
Jul 27, 2025
OpenAI logo
OpenAI
Medium
Software Engineer

Implement a serializable key-value store

Implement in C++ an in-memory key-value store with: - put(key: string, value: string), get(key) -> optional<string>, erase(key). - serialize() -> vect...

Coding & Algorithms
58
0
473 people solved
Jul 15, 2025
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OpenAI
Medium
Software Engineer

Optimize C++ Performance with Provided Concurrency

Given a C++ codebase where threading components (threads, work queues, and synchronization primitives) are already provided, profile and optimize the ...

Coding & Algorithms
10
0
167 people solved
Sep 6, 2025
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OpenAI
Medium
Software Engineer

Implement KV store and plan type conversions

Part 1 — Versioned key-value store: Implement a data structure with set(key, value, t) and get_at(key, t) that returns the value for key whose timesta...

Coding & Algorithms
48
0
371 people solved
Sep 6, 2025
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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
212 people solved
Sep 6, 2025
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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
130 people solved
Jan 10, 2025
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OpenAI
Medium
Machine Learning Engineer

Find earliest supporting dependency version

Question Given a list of dependency versions (e.g. [103.003.02, 103.003.03, 203.003.02]) and a black-box API isSupported(v), design an algorithm to fi...

Coding & Algorithms
66
0
501 people solved
Aug 4, 2025
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OpenAI
Medium
Data Scientist

Identify Bugs in Python Script for User Assignment

Scenario A simple Python script assigns users to experiment groups and triggers the free-trial offer. Question Inspect the script and list any bugs or...

Coding & Algorithms
28
0
87 people solved
Aug 4, 2025
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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
205 people solved
Jul 31, 2025
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OpenAI
Medium
Software Engineer

Implement in-memory DB querying

Question Implement an in-memory database that supports: 1. Querying the whole table and returning only selected columns (projection). 2. Adding WHERE ...

Coding & Algorithms
191
1
663 people solved
Jul 29, 2025
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OpenAI
Medium
Software Engineer Locked

Implement A Contiguous Memory Allocator With Free-Block Coalescing

Review a contiguous memory allocator coding prompt with malloc, free, first-fit allocation, block coalescing, and a best-fit follow-up. The interview ...

Coding & Algorithms
22
1
165 people solved
Jun 5, 2026
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OpenAI
Hard
Machine Learning Engineer Locked

Streaming Entropy with Numerical Stability

This question tests a candidate's ability to implement numerically stable online algorithms for computing Shannon entropy over streaming data. It eval...

Coding & Algorithms
0
0
10 people solved
Jun 3, 2026
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OpenAI
Medium
Software Engineer Locked

Compute Plant Infection Time

This question evaluates a candidate's understanding of graph traversal and grid-based state propagation, including concepts like breadth-first search,...

Coding & Algorithms
3
0
33 people solved
May 24, 2026
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OpenAI
Medium
Frontend Engineer

Build a Streaming Chat Input

Implement a minimal front-end chat interface, similar to a stripped-down AI assistant (think a bare-bones ChatGPT). The user types a prompt, submits i...

Coding & Algorithms
21
0
188 people solved
Apr 25, 2026
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OpenAI
Medium
Software Engineer Locked

Build a File-Backed Key-Value Store

This question evaluates a candidate's understanding of persistent key-value storage, in-memory versus on-disk state management, serialization/deserial...

Coding & Algorithms
6
0
63 people solved
Apr 11, 2026
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OpenAI
Easy
Software Engineer

Implement Chat Event Counter

Design an in-memory counter for chat activity. You need to implement a class with the following two methods: `text processEvent(userId: string, chatId...

Coding & Algorithms
2
0
24 people solved
Apr 10, 2026
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OpenAI
Hard
Machine Learning Engineer

Simulate Plant Infection With Controlled Burning

You are given an R by C grid of plants. Each plant is initially healthy, infected, recovered, or dead. A plant has up to four orthogonal neighbors. De...

Coding & Algorithms
2
0
9 people solved
Apr 2, 2026
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OpenAI
Medium
Software Engineer Locked

Minimize deaths in spreading plant infection

This question evaluates a candidate's ability to model and simulate dynamic grid processes, reason about infection propagation and delayed state chang...

Coding & Algorithms
100
0
1051 people solved
Apr 1, 2026
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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

Frequently Asked Questions

How difficult are OpenAI Coding & Algorithms interview questions?
OpenAI Coding & Algorithms questions are often described as medium-to-hard in difficulty and emphasize practical engineering judgment as much as algorithmic correctness. Expect problems that require clean, testable code, attention to edge cases, and a clear discussion of time and space complexity rather than obscure puzzle tricks. Interviewers frequently push candidates to adapt solutions for production constraints, performance trade-offs, and maintainability, so preparation should cover both problem solving and engineering reasoning.
What does the typical OpenAI interview process look like, and where do Coding & Algorithms questions appear?
The usual process starts with a recruiter screen, followed by one or more technical assessments that vary by role, and culminates in final interviews that include coding, system design, and behavioral rounds. Coding and algorithms work commonly appears in the technical phone screen and in one or more live coding sessions during the final loop; some teams also use take-home exercises or pair-programming assessments. Interviewers evaluate correctness, performance, readability, and testing practices alongside communication and collaboration.
What is a sensible prep timeline to get ready for OpenAI Coding & Algorithms interviews?
A sensible timeline depends on your starting point, but many candidates follow a six- to eight-week focused plan if they have solid foundations, while those needing refreshes may take three months. Early weeks should reinforce core data structures and algorithm patterns and include timed practice in a shared editor; middle weeks should combine medium-to-hard problems with mock interviews and system-oriented algorithm questions; final weeks should emphasize code quality, testing, and rehearsing clear explanations. Recruiters often move candidates through stages in a few weeks, so align your prep with expected scheduling.
Which subtopics within Coding & Algorithms should I prioritize for OpenAI interviews?
Prioritize robust fundamentals like arrays and strings, hash maps and sets, tree and graph traversals, dynamic programming, and complexity analysis, while also practicing problems that bridge algorithms with real-world engineering such as caching, streaming, or rate-limiting logic. Equally important are writing readable, well-tested code and explaining trade-offs as you optimize. For many roles you should also be comfortable reasoning about scalability, correctness under edge cases, and how algorithmic choices affect production behavior. Practice problems that prompt you to move from a correct solution to a production-ready design.
What standout tips and common pitfalls should I know when preparing for OpenAI Coding & Algorithms interviews?
Standout tips include practicing in the same environment used by interviews, narrating your thought process clearly, writing concise tests and handling edge cases, and demonstrating trade-off reasoning when you optimize. Avoid common pitfalls like rushing to code without a plan, ignoring input validation and null cases, overfitting to toy examples, or sacrificing readability for micro-optimizations. Interviewers value pragmatic, maintainable solutions and strong communication, so balance algorithmic correctness with engineering hygiene and be ready to iterate on feedback during the session.

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