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Uber interview notes, page 7 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·Product Manager·Hiring Manager Screen

Apr 2026
Quick PM screen at Uber, basically one estimation question about their core delivery product. Not much to report but it's a useful data point if you're prepping for Uber PM roles.
  • Estimate how many deliveries Uber Eats completes in a day globally.

“Classic estimation question, but I fumbled the structure a bit.”

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Uber·Software Engineer·Technical Phone Screen

Apr 2026
Uber SWE coding round with a task assignment optimization problem. Pretty clean problem once you see the greedy insight, but it's the kind of thing that looks harder than it is under pressure.
  • You have n tasks, each with a different reward depending on whether person 1 or person 2 does it. Person 1 must be assigned exactly k tasks, person 2 gets the rest. How do you maximize the total reward?

“I stared at this for a bit and started thinking about sorting by reward1 descending, which was wrong.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Uber software engineer interview focused on a deep dive into a past project, covering system design, a tricky integration, a technical decision, and retrospective reflection. The format felt more like a technical debrief than a traditional interview, which I wasn't fully prepared for.
  • Walk me through a large project you worked on. Draw a high-level diagram of the system and explain how data or requests flow through it end to end.
  • Describe a complex piece of work from that project, like a non-trivial API integration. How long did it take, and what made it complicated? Be ready to defend your timeline.
  • Tell me about a key technical decision you made on that project. What were the options and why did you choose what you did?
  • Looking back at that project, what would you do differently?

“I'd done this kind of question before but never with an actual diagram component.”

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Uber·Software Engineer·Technical Phone Screen

Apr 2026
Uber SWE interview with a permutation problem that looked deceptively simple at first glance. The core challenge was figuring out an efficient way to check prefix completeness across all k values simultaneously.
  • You're given a permutation of length n containing exactly the elements 1 through n with no duplicates. For each value k from 1 to n, determine whether k is 'balanced', meaning there exists some contiguous subarray whose elements are exactly the set {1, 2, ..., k}. Return a binary string of length n where 1 means balanced and 0 means not.

“My first instinct was to brute force it: for each k, slide a window of size k and check if the min is 1 and max is k with no gaps.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Product sense question for a PM role at Uber, specifically framed around UberEATS. Just the one question but it has a lot of surface area if you let it.
  • You're a PM at UberEATS. What feature would you build to increase the average order value?

“I went straight to upsell mechanics, like bundling drinks or suggesting add-ons at checkout, which felt obvious in retrospect.”

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Uber·Software Engineer·Technical Phone Screen

Apr 2026
Uber SWE interview with a dynamic programming / greedy problem involving a jump game with unusual movement rules. The problem had a tricky constraint I hadn't seen before and I'm still not 100% sure I handled it optimally.
  • Given an integer array, start at index 0 and reach the last index to maximize your total score. From any position i you can move to i+1, or jump directly to any index whose value ends in 3 (like index 3, 13, 23, etc.). You must land exactly on the last cell. What's the maximum score you can collect?

“The i+1 movement is obvious but the 'jump to any index ending in 3' rule threw me off at first.”

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Uber·Software Engineer·Technical Phone Screen

Apr 2026
Uber SWE coding round, one problem the whole session. It looked like a grid puzzle at first glance but the gravity mechanic at the end is what trips people up if they're not careful about order of operations.
  • Given a 2D grid where each cell holds a color value or zero, implement one round of a game mechanic: first identify all cells that should explode (a nonzero cell explodes if at least two of its four orthogonal neighbors share its value), set those cells to zero simultaneously, then apply gravity so nonzero values in each column fall to the bottom while preserving their relative order. Return the resulting grid and analyze the time and space complexity.

“The explosion detection part was fine, I flagged the cells in a separate pass so I wouldn't modify the board mid-scan.”

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Uber·Software Engineer·Onsite - Coding / Algorithms

Apr 2026
Coding round at Uber for a software engineer role. Two problems total, one of which I'd already seen in the phone screen, so I asked to swap it out mid-interview.
  • Given a string like '1-4-3-8', parse and process it according to the problem constraints.
  • Find the maximum square area in a given grid or matrix.

“Already seen this one in the phone screen, so I finished it pretty fast and just asked to move on.”

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Uber·Software Engineer·Technical Phone Screen

Apr 2026
Uber coding interview with a staircase optimization problem that looks deceptively simple until you realize the walking cost is energy-dependent and the whole thing needs a binary search approach. Pretty niche problem, not your typical LeetCode grind.
  • You have a staircase of N floors. You can take an elevator for the first x floors (gaining energy and spending fixed time per floor), then walk the rest (spending energy and spending time that depends on your current energy). Find the value of x that minimizes total time.

“The energy-dependent walking cost is what makes this tricky.”

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Uber·Data Scientist·Technical Phone Screen

Apr 2026
Uber DS interview that went deep into survival analysis for rider behavior modeling. The question was essentially one long technical prompt, and they expected you to hold the whole thing together without much scaffolding.
  • How would you model rider abandonment as a function of how long they've already been waiting? Walk through the survival analysis setup including S(t), h(t), relevant covariates, censoring, and your choice of model.
  • How do you check whether the proportional hazards assumption holds, and what do you do if it doesn't?
  • How would you handle time-varying covariates in this survival model, for example if the quoted ETA updates while the rider is waiting?

“This is a meaty one.”

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