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OpenAI interview notes, page 40 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
OpenAI software engineer interview with a system design coding question that was more implementation-heavy than I expected. Not a pure whiteboard theory session, they actually wanted working code.
  • Build an in-memory key-value store with set, get, shutdown (which flushes all data as bytes to a storage medium), and restore (which reloads that data back into memory).

“The set/get part took me about two minutes.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
OpenAI software engineering interview focused on a pretty deep optimization problem around an IPv4 iterator. One question but they really wanted you to think through every layer of it.
  • You have an IPv4 iterator class that supports forward and backward iteration over a CIDR range, returning addresses as strings. How would you optimize it for both time and space complexity?

“This one took me a minute to get fully into.”

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OpenAI·Backend Engineer·Technical Phone Screen

May 2026
Went through a technical phone screen for a backend role at OpenAI and got hit with a grid BFS problem. Pretty standard if you've seen the rotting oranges problem before, but the edge cases can trip you up if you're not careful.
  • You're given an m x n grid where some cells start infected and the rest are healthy. Each minute, any healthy cell touching an infected one (up/down/left/right) also becomes infected. Return the minimum number of minutes until all cells are infected, or -1 if some healthy cell can never be reached.

“Classic multi-source BFS setup.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a SWE role, focused on building something like Google Calendar. The core challenge was less about CRUD and more about how you handle sync across devices and serve different calendar views efficiently.
  • Design a calendar application like Google Calendar that supports multiple views (day, week, month, year) and syncs updates across devices in near real-time.

“I started with the data model and event storage which felt fine, but the real pressure came when they pushed on the sync part.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
Coding round at OpenAI for a software engineer role, one problem centered on building a chatbot system. The problem wasn't technically brutal but the real test was whether your design could handle future changes without touching existing code.
  • Implement a ChatApp class that manages user messages and bot responses, designed so that new bot types can be added later without modifying existing code.

“I got the core logic down fine but the bot registration part tripped me up.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
OpenAI software engineering interview that was essentially a system design question dressed up as a coding problem. You're building a mini in-memory database from scratch and then they start pulling on threads about indexes and query extensibility.
  • Design and implement a simple in-memory database that stores records with multiple fields and supports filtering by any column value. Walk through your API design choices and how you'd extend it to handle compound AND/OR filters and indexed lookups.

“Started with a straightforward insert/query interface, dict keyed by id, and a linear scan over all records to match filters.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at OpenAI for a software engineer role. The whole session was basically one giant question about payment infrastructure, and they went deep fast.
  • Design a payment processing system that can handle tens of thousands of transactions per second, supports multiple payment methods, integrates with external payment providers, and guarantees no double charges.

“This one sprawled in every direction.”

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OpenAI·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a software engineering role at OpenAI and got a grid-based BFS problem that was a twist on the classic infection spread question. The immune cell wrinkle was subtle but changed how you think about neighbor filtering.
  • You have a grid containing empty cells, infected cells, and immune cells. Each day, every infected cell spreads to its 8 neighboring empty cells, but immune cells can never be infected. How many days until the infection stops spreading? Walk through how you'd modify a BFS approach to handle this.

“I'd done the basic version of this before so I jumped into BFS pretty fast, which was probably the wrong move because I initially forgot to filter out immune cells and just treated them like walls.”

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OpenAI·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at OpenAI for a software engineering role. The whole interview was basically one giant question about LLM inference infrastructure, and it went deep fast. Not a casual conversation.
  • Design a system that serves large language model inference requests at scale. Walk through the full request path from API gateway to model workers.
  • How would you implement batching to keep GPU utilization high while still meeting per-request latency targets like time-to-first-token and time-per-output-token?
  • What latency optimization techniques would you apply to an LLM serving stack?
  • How would you scale the GPU pool and manage costs, including mixing on-demand and spot instances and routing across multiple models?
  • How do you handle reliability concerns like overload, cascading failures, and multi-region availability in an LLM serving system?
  • What observability would you build into this system and how do you think about the cost tradeoffs of different monitoring approaches?

“I started with the API gateway and worked toward the GPU pool, covering auth, quota enforcement, and a request queue in between.”

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OpenAI·Software Engineer·Technical Phone Screen

Jun 2026
Interviewed for a software engineering role at OpenAI and got a pretty deep coding question around serialization. Not a LeetCode grind session, more of a 'show me you understand how the web and JS actually work' kind of thing.
  • Implement a toString utility that can serialize DOM-like node objects (with tag names, attributes, and children) as well as JavaScript functions back into readable string form.
  • How would you handle circular references and bound functions as edge cases in your serialization utility?

“The DOM serialization part felt manageable at first.”

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