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Uber interview notes, page 21 of 61

Large Enterprises

Most of these Uber write-ups come from Software Engineers (407), then Data Scientists (78) and Machine Learning Engineers (65). The most reported rounds are the technical phone screen (387), the system design round (95), the product sense round (46) and the onsite coding round (23).

609 interview notes · updated Aug 2026

Uber·Software Engineer·Onsite - Coding / Algorithms

May 2026
Uber's 2026 onsite for SWE includes a new AI-assisted debugging round where you're dropped into a small full-stack app with a planted bug and expected to fix it using an in-browser AI tool. The session transcript of your prompts is part of the grade, which I did not fully appreciate going in.
  • A small full-stack app is preloaded in the IDE with a broken transaction feature. The interviewer describes a failing scenario (e.g. account transfers sometimes produce the wrong final balance) and asks you to diagnose and fix the bug using the AI assistant.
  • After diagnosing the bug, you may be asked to implement a small additional feature on top of the same codebase.

“The part nobody warned me about: the prompt transcript is graded.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

May 2026
Uber PM interview with a product sense question focused on the airport experience. Pretty open-ended, which I wasn't fully prepared for.
  • How would you improve the airport experience for passengers, specifically around the pain point of time spent waiting?

“I went straight to the obvious stuff, security lines, boarding delays, and kind of lost the thread on what Uber could actually own versus what's just the airport's problem.”

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Uber·Software Engineer·Onsite - System Design / Architecture

May 2026
Uber system design round for a software engineering role, and this one was a full-on design problem around room allocation. Pretty dense question with a lot of moving parts, more than I expected for a single session.
  • Design a room allocation service that takes a meeting request (time window, duration, capacity, required equipment, location) and returns a ranked list of available rooms. Walk through your scoring function, data sources, how you'd tune the weights, safeguards against certain teams always getting the good rooms, and how you'd evaluate the system online and offline including an A/B testing plan.

“This question is basically five questions stapled together.”

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Uber·Software Engineer·Onsite - Coding / Algorithms

May 2026
Uber SWE coding round, got a quad tree construction problem. Not the hardest thing in the world but there were enough edge cases to keep me on my toes for a bit.
  • Given an n x n binary matrix where n is a power of 2, build and return the root of a quad tree representing it. Uniform regions become leaf nodes; non-uniform ones split into four quadrant children.

“My first instinct was to just scan each subregion naively every time, which works but gets slow on bigger grids.”

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Uber·Software Engineer·Onsite - Coding / Algorithms

May 2026
Uber coding round for a software engineer position. The problem was a tree-based palindrome path counting question that looked manageable at first but has some real bite to it once you think about the query complexity.
  • You're given an undirected tree where each node stores a single character. For each query node, count how many nodes on the path from that node up to the root produce a substring (from the query node to that ancestor, inclusive) whose characters can be rearranged into a palindrome. Design an efficient solution that handles multiple queries.

“The palindrome condition is the part that trips you up first.”

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Uber·Software Engineer·Onsite - Coding / Algorithms

May 2026
Uber SWE coding round, got a range-query problem that looked straightforward but has a subtle edge case that'll trip you up if you're not thinking about it carefully. Nothing behavioral, just the one algorithmic problem.
  • You're given an integer array and a list of range queries, each specifying a range and a max decrement value. For each query you can subtract any amount up to that value from each index in the range. Can you always reduce the entire array to zeros by applying all the queries?

“My first instinct was to just simulate it, sum up the total capacity per index and compare to nums[i].”

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Uber·Software Engineer·Technical Phone Screen

May 2026
Phone screen for a Software Engineer role at Uber. One algorithm question, wrong intuition, wrong data structure, round over.
  • Given a problem involving high-frequency tag or label counting, implement a solution using a monotonic queue.

“My first instinct was a heap and I was pretty confident about it.”

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Uber·Software Engineer·Technical Phone Screen

May 2026
Uber software engineering interview that started with a resume walkthrough and then went straight into a meaty behavioral/technical hybrid question about system design trade-offs. Pretty standard format but the question itself had some real teeth to it.
  • Walk me through your resume.
  • Describe a time you made a system design decision that required weighing competing trade-offs. What were the tensions involved, how did you reason through the options, what did you actually change, and what came out of it?

“Routine opener.”

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Uber·Product Manager·Onsite - Behavioral / Leadership

May 2026
Interviewed for a PM role at Uber and got asked about shipping a feature and how I drove its prioritization. Pretty standard behavioral territory but the follow-up pressure made it more uncomfortable than I expected.
  • Tell me about a feature you shipped and how you influenced its prioritization.

“I went in thinking this was a simple 'tell me a win' question and kind of fumbled the prioritization angle.”

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Uber·Software Engineer·Technical Phone Screen

May 2026
Uber SWE coding round, got a graph shortest path problem with a twist on stop constraints. Pretty standard fare for a tech interview but the edge cases kept me second-guessing myself the whole way through.
  • Given a list of directed flights with prices between n cities, find the cheapest route from a source city to a destination city using at most k stops. Return -1 if no valid route exists.

“My first instinct was plain Dijkstra but then the stop constraint throws a wrench in it because you can't just track visited nodes the usual way.”

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