OpenAI interview notes, page 6 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·Product Manager·Onsite - Product Sense / Strategy

Apr 2026

PM interview at OpenAI with a single product strategy question. The premise was wild enough that I spent the first 30 seconds just trying to figure out if it was a joke.

You're a startup that has built technology capable of translating human speech and text into animal language. How do you bring this product to market?

“The absurdity of the premise almost made me lose the thread entirely.”

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OpenAI·Software Engineer·Technical Phone Screen

Apr 2026

OpenAI SWE interview with a multi-part algorithmic problem built around plant infection spreading on a grid. The whole session was one problem with five progressively harder sub-questions layered on top of each other, which I wasn't really expecting.

Given a grid where some plants start infected, find the total time for infection to spread to all plants using simultaneous level-by-level propagation, or return a sentinel value if it's impossible.
For the same grid setup, return the earliest time each individual cell gets infected.
Extend the infection model to support multiple independent infection sources starting at different times.
Add obstacles to the grid that block infection from spreading through them. How does this change your approach?
Given a series of queries each asking whether a specific cell is infected by a specific day, answer them efficiently.

“Classic BFS from multiple sources at once.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

Apr 2026

System design round at OpenAI for an infrastructure role. The question was a full-blown video storage platform design, YouTube-scale, and they clearly wanted you to go deep on every layer rather than just sketch boxes on a whiteboard.

Design a large-scale video publishing and storage system similar to YouTube, covering the full pipeline from upload through playback at over a billion videos.

“This one sprawled in every direction fast.”

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OpenAI·Software Engineer·Technical Phone Screen

Apr 2026

Interviewed for a software engineering role at OpenAI and got hit with a stateful balance-tracking problem that looked deceptively manageable at first glance. The sticky-None behavior is where things get interesting and where I almost tripped up.

You have a table of adjustments with an id, a numeric value, a start time, and an optional stop time. Write a function check(t) that returns the sum of all active entries at time t, where an entry is active if start <= t < stop (no stop means it's still active). Return None if the total is negative, return 0 if nothing is active, and once any call has returned None, all future calls must also return None regardless of what the actual total would be.

“The interval logic and the None-for-negative part were fine, I got those pretty quickly.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

Apr 2026

Went through a system design round at OpenAI for a data engineering role. The whole thing was essentially one massive question about building a hybrid streaming and batch pipeline, and they really wanted you to go deep on every layer. Felt like drinking from a firehose.

Design a data pipeline that handles both low-latency streaming and high-throughput batch workloads. Walk through ingestion, processing, storage, and how you'd handle the trade-offs between the two approaches.
How do you guarantee exactly-once semantics in a streaming pipeline, and when would you accept at-least-once instead?
How do you handle late-arriving data in a streaming system? What role do watermarks play and what are their limitations?
How would you approach schema evolution in a pipeline where multiple consumers depend on the same data stream?
Walk through how you'd design and execute a backfill when your batch pipeline logic changes and historical data needs to be reprocessed.
How do you implement data lineage tracking across a complex multi-stage pipeline, and why does it matter operationally?
How would you define SLOs for a data pipeline, and what monitoring would you put in place to detect and respond to violations?

“This was basically the entire interview.”

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OpenAI·Software Engineer·Technical Phone Screen

Apr 2026

OpenAI SWE coding round, one question, grid-based BFS/simulation problem that's been floating around on forums for a while. Nothing too surprising if you've done your prep.

Given an n x m grid containing some initially infected plants, simulate the spread of infection to neighboring cells each day. How many days does it take until no new plants become infected?

“Classic multi-source BFS.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

Apr 2026

OpenAI ML Engineer interview with a numerical computing question that sounds straightforward until you're actually sitting there trying to remember why max-subtraction matters. Pretty technical, no fluff.

Implement a numerically stable softmax function for a 2D NumPy array using vectorized operations, then discuss its complexity, overflow behavior, and how you'd scale it to GPU.

“I knew the subtract-max trick going in but fumbled explaining *why* it works without a loop.”

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OpenAI·Machine Learning Engineer·Technical Phone Screen

Apr 2026

Interviewed for an ML Engineer role at OpenAI and got hit with a NumPy vectorization puzzle. Pretty niche stuff but makes sense given the role. Left feeling okay about it but not totally confident.

Solve an array manipulation problem using only vectorized NumPy operations (broadcasting, slicing, boolean masking) with no explicit Python loops, then discuss the time and space complexity of your solution.

“This tripped me up more than I expected.”

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OpenAI·Software Engineer·Recruiter / HR Screen

Apr 2026

Recruiter screen for a software engineer role at OpenAI. Pretty standard stuff, two main questions about motivation and background, but OpenAI's mission makes the 'why us' question feel higher stakes than usual.

Why do you want to work at OpenAI, and why are you interested right now specifically?
Walk me through your background: your current role, notable projects, technical strengths, and what you're looking for next.

“This one tripped me up more than I expected.”

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OpenAI·Software Engineer·Technical Phone Screen

Apr 2026

OpenAI SWE interview with a concurrency debugging question on an in-memory cache. Pretty deep technically, they wanted you to actually reason through the race conditions rather than just name-drop solutions.

You're given an in-memory cache (like a get-or-load or LRU cache) that works fine single-threaded but breaks under concurrent access. Find the concurrency bugs, fix them, explain the root cause, and discuss how well your fix scales across different locking strategies.

“This one took me a minute to get going.”

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