1p3a Experience · May 2026

openai lead machine learning engineer tech phone screen experience

MLE Phone Screen newgrad
2 upvotes 5 replies

Interview Experience

两轮 第一题变形金刚捉虫,我只找到了3个bug,有一个死活找不出来,最后他告诉我,其实是一个typo,把v改成y就行了,我半天没看到... 第二题植物感染题,只做到3道题。他们的IDE让我很不习惯,一直写错代码... 我觉得我几乎投入了两周很多时间来复习,以上两道题目几乎做烂,到面试的时候,我居然像得了失心疯一样。😭 我可能太紧张了,总而言之心态崩了。

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About OpenAI Interview Reports

This question was reported by a candidate who interviewed at OpenAI. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at OpenAI are the higher-signal extractions to take from this report.

For broader preparation context, the OpenAI interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in OpenAI reports consistently are the ones worth investing in; one-off niche problems are not.

During Your OpenAI Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in OpenAI reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.