OpenAI interview notes, page 63 of 67

Mid-sized

Most of these OpenAI write-ups come from Software Engineers (460), then Machine Learning Engineers (137) and Backend Engineers (23). The most reported rounds are the technical phone screen (335), the system design round (229), the onsite coding round (32) and the behavioral / leadership round (22).

667 interview notes · updated Jul 2026

OpenAI·Machine Learning Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at OpenAI for an ML Engineer role, focused entirely on dynamic pricing for a ride-hailing platform. Pretty open-ended and they kept pushing on production concerns more than I expected.

How would you design a pricing strategy for a ride-hailing platform that balances rider experience, driver supply, and overall marketplace efficiency?
Design a production system that computes and applies surge pricing multipliers in near real time, with updates every one to five minutes.
How would you prevent extreme volatility in surge pricing, like rapid spikes or oscillating multipliers?
How would you make your surge pricing system robust to fraud and sudden demand shocks like major events or extreme weather?
What metrics would you track to monitor the surge system, and how would you run experiments to validate changes to the pricing model?
What safety constraints and edge cases would you build into the surge pricing system?

“I went straight to supply/demand ratio as the core signal, which felt right, but I fumbled when they asked how I'd actually weight rider experience against marketplace efficiency.”

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OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

Interviewed for a data science role at OpenAI, got asked a stats fundamental that sounds easy until you actually have to explain it clearly under pressure.

What is a p-value?

“I know what a p-value is.”

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OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

OpenAI Research Engineer interview with a coding round focused on a text editor autocomplete problem. The question had real depth to it, combining data structures with stateful mutation, which made it harder than it looked on the surface.

You're building an autocomplete feature on top of a text buffer that supports insert and delete operations. Implement a suggest(prefix, k) function that returns the top-k most frequently inserted words starting with that prefix. Word frequency should go up on insert and down on delete, and you need to keep retrieval efficient as the buffer keeps changing.

“My first instinct was trie plus a heap, which is fine but I fumbled the deletion part pretty badly.”

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OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

SQL-heavy technical screen for a SWE role at OpenAI. Four sub-problems, all on the same two tables, ramping from basic aggregation up to a rolling window function. Nothing crazy conceptually but the scale constraints made you think twice about how you'd actually run this in prod.

Given a users table with country info and an events table, write a query to count how many users exist per country.
Using the same tables, compute daily active users by counting distinct users per calendar day derived from the event timestamp.
For each user, return their very first event time and the type of event that occurred at that time.
For each country, calculate a 7-day rolling count of distinct active users per day, ordered chronologically. You can use window functions.

“Straightforward GROUP BY.”

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OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

A technical screen for a software engineering role at OpenAI that went deep into C++ performance optimization. The whole thing was basically one long question about profiling and tuning a multithreaded codebase, which sounds manageable until you're actually in it.

You're given a C++ codebase with threading primitives already provided. How would you profile it, identify bottlenecks, and optimize for both throughput and latency?
What concrete code-level changes would you make to address memory allocation patterns, unnecessary copying, and branch misprediction in a performance-sensitive C++ system?
How would you minimize lock contention and maintain correctness in a concurrent system without writing the synchronization primitives yourself?
How would you validate both performance improvements and correctness in a concurrent C++ program after making optimizations?

“This is where I spent most of my time and also where I felt most out of my depth.”

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OpenAI·Product Manager·Onsite - Product Sense / Strategy

Jul 2026

Interviewed for a PM role at OpenAI, got asked about AI search and its broader impact. Pretty thin on details but the question itself had some depth to it.

What is the impact of AI search on the market and on users?

“Broader than it sounds.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

Jul 2026

OpenAI system design round, one meaty problem that took up the whole session. The shard balancing question sounds straightforward until you actually start coding it and realize the objectives are in tension with each other.

You have a set of shards with associated loads distributed across nodes. Design and implement an algorithm to rebalance those shards so that load imbalance is minimized while keeping the number of shard moves as low as possible. Walk through your objectives, constraints, and the trade-offs between move cost and balance quality.

“The part that tripped me up was that 'minimize imbalance' and 'minimize moves' pull in opposite directions and you can't fully satisfy both.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

Jul 2026

One round of coding for an MLE role at OpenAI, focused entirely on debugging a distributed system. The question was pretty gnarly and I hadn't seen anything like it on the usual prep sites.

You're given a buggy Python job scheduler. Identify and fix issues related to data races, deadlocks, and lock contention, verify the rate limiter logic is correct, write your own test cases to confirm it works, then compute the scheduler's job-scheduling time and success rate.

“This one was a lot.”

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OpenAI·Software Engineer·Technical Phone Screen

Jul 2026

Applied for a Software Engineer role at OpenAI and hit a system design screen on Chess. Felt decent about it, then found out there'd be a second SD round anyway.

Design a system to support a Chess application.

“Walked through it and thought I covered the bases pretty well.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at OpenAI, one big sprawling question about notification infrastructure. The scope was genuinely intimidating and I don't think I covered everything they wanted.

Design a real-time notification system that supports push, email, SMS, and in-app channels at massive scale (100M+ users). Walk through event ingestion, how you'd abstract across channels, user preferences and opt-outs, deduplication, retry logic with a dead-letter queue, cross-channel fallback, delivery SLAs, fan-out architecture, your data model, gradual rollout and A/B testing hooks, observability, and abuse prevention.

“This was basically one question that kept expanding.”

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