1p3a Experience · May 2026

uber onsite software engineer interview experience

SWE Onsite newgrad
1 upvote 5 replies

Interview Experience

以下内容需要积分高于 200 您已经可以浏览 coding 1: LRU cache coding 2: 题目:给员工安排座位,条件是让每个员工坐得尽量远,而且安排好之后不能改。 下面的 expected output 是我跟面试官确认了的。没做出来,不知道LC上有没有。 class AssignSeat: def init(self, n): pass def assign(self): pass // expected output: seats = AssignSeat(10) seats.assign() -> 0 seats.assign() -> 9 seats.assign() -> 4 or 5 sd: 非常nice的国人小哥,开始直接讲中文,很亲切。给我选了相对简单的 Tiny URL ,都是常规问题。面试用的英文。 hm: 讲一个past project ,bq都没咋问。75分钟的面试,太久了,大家做好准备。 发面经攒人品!加...

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About Uber Interview Reports

This question was reported by a candidate who interviewed at Uber. 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 Uber are the higher-signal extractions to take from this report.

For broader preparation context, the Uber 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 Uber reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Uber 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 Uber 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.