"Tell me about a time you optimized a piece of code that was causing performance issues in production on a mobile app. I’d like a specific example where the issue affected real users, how you diagnosed it, how you prioritized the fix against other work, and what happened after you shipped the improvement. If relevant, you can use an example from ChatGPT for iOS or Android, or a similarly high-traffic mobile product."
This question is not just about whether you can write faster code. It tests whether you take ownership of production quality, can work through ambiguity when the root cause is unclear, and can make sound trade-offs under pressure. For a Mobile Engineer at OpenAI, interviewers want to see that you can connect technical performance work to user impact, collaborate across engineering and product, and improve the system without creating regressions.
A strong answer is specific: name the surface, the symptom, the scale of impact, the diagnosis process, and the exact optimization you made. The best responses show structured prioritization, data-driven decision-making, and a clear result with metrics, plus one lesson you carried forward into future mobile development.