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Uber interview notes, page 43 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

Jun 2026
Uber coding round for a software engineer role, pretty much one meaty algorithmic problem that took up the whole session. The problem was interesting but the pressure to also explain tradeoffs out loud while coding made it trickier than expected.
  • Given a list of packages and their build dependencies, produce a valid build order such that every package is built only after its dependencies. If no valid order exists due to a cycle, report that. You also need to explain your algorithm, analyze complexity, handle disconnected components and duplicate dependencies, and compare a BFS in-degree approach with a DFS post-order approach.

“This is basically topological sort dressed up in a packaging scenario, which I recognized pretty fast.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026
Uber SWE interview that leaned heavily on graph theory and systems thinking. The coding problem was straightforward on the surface but the follow-up about production failure handling is where things got real.
  • Given N services and a list of dependency pairs where (A, B) means B must deploy before A, find a valid deployment order for all services. If a cycle exists, detect it and return something meaningful. Walk through your approach, implement it, and analyze the complexity.
  • How would you handle partial deployments, retries, and failure recovery in a real production environment for this kind of service dependency system?

“I went with Kahn's algorithm because BFS feels more intuitive to explain out loud than recursive DFS.”

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Uber·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Uber MLE interview with a focused experimentation question. Pretty technical but not in a coding sense, more like they wanted to see if you actually understand when and why you'd pick a given statistical test.
  • You're running a user-level A/B test on a continuous metric like order value or session length. Why is a two-sample t-test appropriate here, and walk through how you'd actually run it end to end.
  • Under what conditions would you abandon user-level randomization and run a switchback or geographic experiment instead?

“I knew the mechanics well enough but stumbled a bit explaining the 'why' before the 'how'.”

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Uber·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Bizops interview at Uber with a macro strategy question about Uber Eats. Single question, pretty open-ended, felt more like a case prompt than a standard interview question.
  • What are two macroeconomic trends that could affect supply or demand for Uber Eats in the near future?

“I went with inflation squeezing consumer discretionary spending and gig worker supply shifting as unemployment rates change.”

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Uber·Data Scientist·Technical Phone Screen

Jun 2026
Uber DS interview with a meaty product experiment question about a rider-incentive program. The whole thing was one big case and they kept pushing for more depth on every layer.
  • Design an experiment to measure the impact of a new rider-incentive program. Walk through your metrics for riders, drivers, and overall marketplace matching quality, what else you'd add and why, and how you'd measure effects without knowing much about how the feature works internally.

“This one sprawled in a way I wasn't ready for.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Uber for a software engineer role. The whole thing was basically one giant question about building a ride-hailing platform from scratch, covering everything from matching algorithms to payment durability. Dense but fair.
  • Design the backend for a large-scale ride-hailing platform similar to Uber, covering architecture, data modeling, matching, real-time tracking, scalability, and fault tolerance.

“This was the entire interview.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026
Uber SWE interview with a DP problem that looked simple on the surface but had this weird constraint about prime numbers ending in 3. Not a round I felt great leaving.
  • You're given an integer array and start at index 0. At each step you can move 1 cell to the right, or jump forward by any prime number whose last digit is 3 (so 3, 13, 23, 43, and so on). You accumulate values at every cell you land on. What's the maximum sum you can collect by the time you reach the end?

“The jump rule is what got me.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026
Uber SWE coding round with a graph/union-find problem that looks deceptively straightforward until you hit the scale constraints. The O(n^2) naive approach gets you partway through the reasoning but TLEs, so the whole interview basically pivots around whether you can figure out the smarter grouping strategy.
  • You have a list of balls at 2D integer coordinates and a distance threshold d. Two balls connect if they share a row or column and their coordinate difference along that axis is at most d. When you trigger a ball, it pulls in everything connected to it transitively. What is the minimum number of triggers needed to collect all balls?

“My first instinct was union-find, which was right, but I went straight to checking every pair and the interviewer let me code it up before pointing out the scale.”

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Uber·Software Engineer·Technical Phone Screen

Jun 2026
Uber SWE interview that went deep into data structure design, specifically around streaming frequency tracking. The kind of problem that sounds manageable until you're actually on the spot trying to justify every complexity claim.
  • Design a data structure that tracks the top-K most frequent keys in a stream, supporting increment, decrement, and topK operations with O(1) amortized updates.

“I knew the hash map part immediately but fumbled explaining why the doubly linked list of frequency buckets actually gives you O(1).”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Uber for a software engineering role. One question, no fluff.
  • Design a stock trading platform similar to Robinhood.

“This is a meaty one.”

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