Interview Experiences

Real candidates, real loops: every round, what was asked, and how it ended.

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53 stories

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OpenAISoftware Engineer
Jun 2026

In-Memory Malloc/Free Allocator, First-Fit to Best-Fit

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Technical ScreenXP0
OpenAISoftware Engineer
Jun 2026

A Coding Question With Zero Existing Writeups Online

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RejectedOnsiteXP0
OpenAISoftware Engineer
May 2026

An Extra System Design Round on a 'Build Cache' Question I Never Understood

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Technical ScreenXP0
OpenAIAndroid Engineer
May 2026

System Design and UI Screens in One Afternoon, Stuck on a Layout

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RejectedTechnical ScreenXP0
OpenAIMachine Learning Engineer
May 2026

A 60-Minute Infection-Spread Simulation, Four Parts

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Technical ScreenXP0
OpenAIBackend Engineer
Apr 2026

Tricky IDE Quirks and a Surprise Chess Game System Design

Let me start by saying you should try to avoid this interviewer if you can. He had a really heavy accent and I couldn't understand him at all, and when I asked questions partway through the interview, he just kept going silent. The question was the IP address problem. I got to the third part, the CIDR block part, but when I ran it the answer was wrong. After the interview ended I thought about it…

Technical Screen0
OpenAIMachine Learning Engineer
Apr 2026

A malloc Phone Screen and a Surprise Debugging Round

Sharing an OpenAI interview report. Aside from the phone screen, everything was a question I'd already seen before — because I over-prepared from question banks and cared way too much about the outcome, I interviewed badly. I really regret it. The phone screen covered malloc, which others have already shared — the details aren't much different. There were two parts: first a naive first-fit soluti…

Onsite0
OpenAIMachine Learning Engineer
Apr 2026

Seven-Part Research Onsite, Offer a Week Later

You can find my phone screen writeup in a separate post. Since this was a recruiter reach-out, once I passed the phone screen I went straight to onsite with the team that wanted to interview me. The onsite was split into the following parts: Collaboration interview — we talked about the current SOTA in my research direction, its pros and cons, whether I had relevant technical experience, and how…

OfferOnsite0
OpenAIMachine Learning Engineer
Apr 2026

Task Scheduling and Monster Battle Simulation Coding Rounds

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OnsiteXP0
OpenAISoftware Engineer
Apr 2026

Phone Screen, Onsite, and Way Too Many Reference Checks

I interviewed in April, and only got around to writing this up today. Hope it helps. Phone screen: Coding: Contagion — basically the same as the version posted on the forum. Part 1: only an infected state, how long until everyone gets infected. Part 2: building on part 1, add an immune state. Part 3: after being infected, you become immune after D days — how long until it stabilizes. Part 4: add…

Onsite0
OpenAIMachine Learning Engineer
Apr 2026

Four One-Hour Rounds in a Single Phone Screen

Sharing my recent OpenAI Research phone screen. Round 1: general coding, 1hr Debug a distributed system. They gave me a buggy job scheduler written in Python — I had to check for data races, deadlocks, lock contention, and whether the rate limiter was implemented correctly. Partway through I had to write my own test cases to confirm the scheduler actually worked, then calculate how long the sched…

In progressTechnical Screen0
OpenAIMachine Learning Engineer
Apr 2026

Four Technical Problems, Told Not a Match

Question 1: 1NN This one's got a lot of write-ups already on the forum, so I won't go into detail here. Question 2: Infectious disease The first three parts were exactly the same as what's already on the forum. The fourth part: at any given moment, for a plant that isn't dead yet, if it has >=K infected neighbors, it enters a dead countdown (dies after D days); if it has >=T but <K infected neigh…

RejectedOnsite0
OpenAIMachine Learning Engineer
Mar 2026

A Text Editor That Grew Into Undo/Redo, Autocomplete, and Real-Time Collaboration

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Technical ScreenXP0
OpenAISoftware Engineer
Mar 2026

Distributed Node-Counting System Design Question

I've interviewed with OpenAI several times recently. This question gives you a root node and an initial API, sendAsyncMessage(nodeId, message). You need to implement receiveMessage(fromNodeId, message) yourself, and ultimately count how many nodes exist in the whole network. On the surface it looks a bit like DFS, but it's dressed up as a more realistic distributed scenario. Each node can be thou…

Technical Screen0
OpenAIEngineering ManagerSenior+
Feb 2026

A Slack System-Design Screen That Fell Apart on Scalability

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RejectedTechnical ScreenXP0
OpenAISoftware Engineer
Feb 2026

A Toy Language Coding Question and a Crossword Puzzle System Design

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RejectedTechnical ScreenXP0
OpenAIData Scientist
Feb 2026

A LinkedIn Cold Ask, a Take-Home, and a Python Debug Stumble

I didn't expect to actually get an interview invite from OpenAI — I'd only asked a recruiter about it on LinkedIn. My own level isn't really there, so I went into it purely as an experience, but the experience was great, worth writing up a post-interview reflection. Some background: I do data work at a big company, and my job search has mainly focused on experimentation and causal inference. Afte…

RejectedTechnical Screen0
OpenAIData Scientist
Jan 2026

A Promotion Take-Home, Then a SQL and Python Debugging Round

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Technical ScreenXP0
OpenAISoftware Engineer
Jan 2026

Strong Feedback Every Round, Still Rejected

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RejectedOnsiteXP0
OpenAIData Scientist
Jan 2026

A Free-Month Promotion Take-Home and a Python Debugging Stumble

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Technical ScreenXP0

What are interview experiences?

An interview experience is a candidate's own account of a hiring loop — not a question bank entry. It tells you the shape of the process: how many rounds there were, what each round actually tested, how long the gaps between them ran, and what the recruiter said at the end. That context is the part a question list cannot give you.

How to read them

Weight recent write-ups more heavily — interview loops change, often within a year. Read several for the same company and role rather than one: a single account tells you what one interviewer asked, while five tell you what the bar is. Note the outcome badge too, since a rejection write-up usually explains the gap far more precisely than an offer one.

Share your own

Every published experience earns 50 XP, and each of the first 3 likes it receives in a day earns you 10 XP more. Likes must come from established accounts; like-for-like swaps and likes from your own second account are not paid. Write it while the details are fresh — the round order, the exact prompts, and how much time you were given are what the next reader needs.

Share your experience to earn XP