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OpenAI interview notes, page 24 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·Software Engineer·Technical Phone Screen

May 2026
A/B testing code debug question for an OpenAI SWE role. The prompt gives you broken Python and asks you to find what's wrong, which sounds manageable until you realize how many subtle statistical traps are buried in there.
  • You're given a Python function that runs an A/B test on a user-level DataFrame. Find at least three bugs or statistical pitfalls and explain why each one matters.
  • When would you use a t-test versus a proportion test versus bootstrap versus a non-parametric test for analyzing an A/B experiment?
  • How would you handle missing values in the metric column before running statistical tests on an A/B experiment?
  • What is a sample ratio mismatch (SRM) and how would you detect and handle it in an A/B test?

“The code looks innocent at first glance but there's a lot going on.”

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

May 2026
ML Engineer design interview at OpenAI focused entirely on data strategy for high-dimensional inputs. One long, open-ended question that kept branching into sub-topics. Felt more like a research discussion than a standard interview.
  • You're building an ML system with high-dimensional inputs like long text or high-resolution images. Labels require human annotators, which is expensive. How do you design your data collection and labeling strategy end to end?

“This sprawled in every direction and I wasn't ready for how much ground it would cover.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a software engineer role, focused entirely on building a Slack-like messaging system. The interviewer went pretty deep on edge cases I didn't fully anticipate going in.
  • Design a messaging system like Slack, focusing on sending and receiving messages at scale.
  • How would you handle message ordering in a distributed messaging system?
  • If a client's WebSocket connection drops, how do you ensure they don't miss messages?
  • What are the tradeoffs involved in designing the notification system for a messaging app?

“Went with WebSocket for real-time delivery, which felt like the right call.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

May 2026
OpenAI ML Engineer interview with a debugging-focused coding round. They handed me a broken Transformer classifier and wanted me to fix it, which sounds manageable until you realize how many subtle things can go wrong in a small model.
  • You're given a buggy Transformer-based text classifier. Find and fix the issues so it trains and predicts correctly.

“The part they really cared about was how you collapse the sequence of token embeddings into a single vector before the classification head.”

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OpenAI·Product Manager·Onsite - Product Sense / Strategy

May 2026
Two open-ended product strategy prompts for an OpenAI PM role, both with a lot of moving parts. The animal translation one felt almost like a trick question and the subscription tier prompt was more familiar territory but still had some sharp follow-ups.
  • How would you design an animal-to-human translation product, pick your initial target users, and bring it to market?
  • Why start with dogs specifically rather than another animal or species?
  • What would make the animal translation product unsafe, and how would you guard against it?
  • How would you avoid the product leading users to anthropomorphize animals in harmful or misleading ways?
  • How would you evaluate and launch a new subscription tier priced above the existing Plus plan for an AI assistant?
  • What features or capabilities should stay out of a consumer-facing Pro tier and be reserved for team or enterprise plans instead?
  • How would you detect whether a new higher-priced tier is cannibalizing your existing subscriber base rather than capturing new revenue?

“The scope of this one is deceptively huge.”

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OpenAI·Product Manager·Hiring Manager Screen

May 2026
Interviewed for a PM role at OpenAI, one question about shipping a product or feature.
  • Walk me through a product or feature you shipped from start to finish.

“Pretty standard PM question but I always fumble the scoping.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
ML debugging round for a Research Engineer role at OpenAI. The whole session was a buggy Transformer implementation you had to fix and then extend into a classifier. Pretty intense for a single round.
  • You're given a broken Transformer encoder implementation. Find and fix all the bugs so it trains correctly on a toy task.
  • Now take the fixed Transformer and turn it into a sequence classification model. Add a classification head, swap in cross-entropy loss, write a training loop, and show it converges on toy data.

“There were a lot of moving parts here.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a software engineer role, focused entirely on designing a payment backend. The question was dense and had a lot of surface area, from idempotency to ledger design to reconciliation. Felt like I was constantly being pulled deeper before I finished the previous layer.
  • Design the backend for a payment system that handles customer charges through external payment processors, covering everything from when a user clicks Pay to a confirmed, recorded transaction.
  • A PSP call times out and you never receive a webhook. Walk through exactly how your system converges to the correct state and how long that takes. What does the customer see in the meantime?
  • How do you guarantee exactly-once effect on the customer's card given that both your retries and the PSP's webhooks can deliver the same event more than once?
  • How would you extend this design to route payments across multiple PSPs, for example failing over when one is down or routing by cost, without breaking idempotency or your internal ledger?
  • How do you handle a chargeback or dispute that arrives weeks after the original payment, and how does that get reflected in your ledger?
  • How would you support recurring subscription billing and retry logic for failed renewals on top of this payment core?

“This is the core question and it's massive.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

May 2026
OpenAI ML engineer interview, technical phone screen focused entirely on transformer internals. They gave me a broken implementation and told me to find the bugs. Felt more like a code review than a typical coding round.
  • You're given a transformer model implementation with 5 bugs, each marked in the code comments. Find and fix all of them.
  • Explain what the key-value cache does during autoregressive decoding and why it makes inference faster.

“This was the whole interview basically.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
Did a technical phone screen for a software engineer role at OpenAI. One question, pretty focused, but the edge cases had more depth than I expected going in.
  • Design and implement an in-memory counter for chat activity. You need two methods: one to record a chat event for a given user and chat at a specific timestamp, and one to return how many events for that pair fall within the 15-minute window ending at the most recent recorded timestamp.

“I jumped straight to a nested hashmap keyed on userId and chatId, storing a sorted list of timestamps underneath.”

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