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OpenAI interview notes, page 20 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·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a software engineer role, centered entirely on designing a cloud DevBox platform. Heavy on infrastructure tradeoffs and the kind of question where you can spiral forever if you don't anchor on the right structural decisions early.
  • Design a cloud-based DevBox platform that gives developers disposable or persistent remote development machines accessible via browser, SSH, or IDE plugins. Cover the full lifecycle, multi-tenancy, and how you'd hit aggressive provisioning latency targets.
  • How would you implement pause and resume so that a warm resume completes in single-digit seconds at scale, and what does that cost you in storage?
  • A node dies with multiple running persistent dev boxes on it. Walk through exactly how the system detects the failure, recovers the boxes, and what data-loss guarantee you can actually make.
  • How do you keep secrets out of base images and RAM snapshots while still injecting them at runtime?
  • How does your scheduler decide where to place a new or resuming dev box, and how do you balance avoiding fragmentation against avoiding noisy-neighbor problems?

“The scope here is enormous and I burned probably five minutes just trying to figure out where to start.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
OpenAI SWE technical screen with a distributed systems coding problem. The question was genuinely interesting but also kind of brutal if you've never thought about async message passing as a first-class constraint.
  • You have a directed tree where each node is an independent machine. You can't access the tree structure directly. Using only an async sendMessage/receiveMessage API, design a protocol so that the root node can count the total number of nodes in the tree.

“This one messed with me more than I expected.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a software engineer role, centered entirely on building an online crossword/puzzle platform. The scope was broader than I expected, covering everything from the user-facing API to distributed worker coordination and algorithmic grid solving. Pretty intense for a single session.
  • Design an online crossword puzzle service that can generate puzzles from a word list and grid template, serve users interactively, and handle computationally expensive generation jobs.
  • How would you parallelize puzzle generation across multiple workers, and how do you split the search space efficiently?
  • What happens if a worker crashes partway through a puzzle generation job? How do you recover without starting over?
  • How do you handle bursty load on the puzzle generation pipeline? Walk through your queueing strategy and autoscaling approach.
  • Describe the algorithmic approach for filling a crossword grid, including how constraint propagation fits in.
  • What does the data model look like for this system? Cover the puzzle entity, user attempt state, and your storage choices.
  • What API surface would you expose for the interactive puzzle-playing experience?

“The opening question that basically ate the whole interview.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

May 2026
OpenAI ML Engineer interview with a meaty systems coding question. The whole thing was basically one big design-and-implement problem, which I wasn't fully expecting for this role.
  • Build a tick-based simulation of a coffee-shop queue. The shop has multiple baristas each with their own service time, customers arrive with an arrival time and order complexity, and the system uses a single FIFO queue. Implement a Simulation class with a run() method that returns total customers served, average wait time, and max queue length. The design should allow new event types to be added without rewriting the core loop. Also discuss data structure choices and how you'd extend it to multiple locations or menu tiers.

“I spent the first few minutes just staring at the tick loop logic trying to figure out if I needed a heap or a plain counter for barista availability.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
One round of ML coding at OpenAI for a Research Engineer role, 60 minutes, two parts back to back. The second part is where things get interesting and probably where most people slip up.
  • Implement a 1-Nearest Neighbor classifier from scratch using numpy.
  • Rewrite your 1-NN implementation so that the logic is expressed as neural network weights rather than explicit distance computation.

“Pretty standard starting point.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a data science role at OpenAI and got hit with a pretty meaty experiment design question. Not a lot of hand-holding, they just wanted to see how you think about the messy parts of running experiments in practice.
  • How would you design an experiment to avoid common pitfalls in interpreting results?

“I started with randomization and sample size, which felt safe, but they kept pushing.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
Did a system design round at OpenAI for a software engineer role. First round felt rough, got drilled with follow-up questions I wasn't ready for, and pacing turned out to be a bigger issue than I expected.
  • Design a social network system.

“Prep wasn't the problem.”

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OpenAI·AI Engineer·Technical Phone Screen

May 2026
OpenAI AI Engineer technical screen, one round focused entirely on numerical computing for ML. The problem was deceptively hard once you got past the basic softmax definition, and the streaming extension really separated people who actually understand floating point from people who just memorized formulas.
  • Given a vector of logits, compute the entropy of the softmax distribution in a numerically stable way, avoiding overflow in the exponentiation and underflow in the log.
  • Extend the entropy computation to a streaming setting where logits arrive one at a time. Maintain the entropy incrementally without reprocessing previous logits, and handle the case where a new logit exceeds the current running maximum.

“I knew the log-sum-exp trick going in, so the first part felt okay.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
OpenAI system design round for a software engineering role. The question was about designing Sora, which sounds cool on the surface but quickly turns into a pretty deep conversation about failure handling once you get past the high-level architecture.
  • Design Sora (OpenAI's video generation system), including a high-level system overview followed by a deep dive into the scheduler component and its failure cases.

“The high-level part felt manageable but the scheduler deep dive is where things got real.”

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OpenAI·Data Scientist·Onsite - System Design / Architecture

May 2026
Onsite system design round at OpenAI for a data scientist role. The main question was a deep code review slash experiment reliability problem that required knowing a lot more than just stats. Pretty grueling if you haven't thought carefully about experiment infrastructure before.
  • You're given a Python snippet that randomly assigns users to a trial or control group and triggers a billing API call. Find at least 8 correctness or reliability issues that could corrupt the experiment or its data, and propose concrete fixes for each.

“This wrecked me a little at first because I came in expecting a stats question and got handed code to audit.”

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