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Uber interview notes, page 55 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·Technical Phone Screen

Jul 2026
Uber SWE interview with a classic dynamic programming string problem. Not a lot of context to go on but the question itself is a solid one that trips people up if they haven't seen it before.
  • Given a string, find the minimum number of characters you need to insert to make it a palindrome.

“This is a DP problem but it's easy to go down the wrong path if you start thinking about it greedily.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jul 2026
System design round at Uber for a software engineering role. The whole session was basically one big question about driver queuing at pickup areas, which sounds deceptively simple until you start pulling on the threads around geofencing, consistency, and fairness.
  • Design an internal API that, given a pickup area like an airport curb or venue lot, returns the current ordered queue of drivers waiting in that area.
  • How would you handle the consistency trade-offs between when a driver enters or leaves an area and when that change is reflected in the queue?
  • How would you handle fairness or tiebreaking when two drivers enter the same pickup area at nearly the same timestamp?

“This question has a lot more surface area than it looks.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jul 2026
Uber system design round for a software engineer role. One big open-ended question that basically ate the whole session, no warm-up, no small talk, just dive in.
  • Walk through the full technical design of a significant project you've built: the problem, scale, constraints, your role, architectural decisions and trade-offs, data storage and schema, interfaces, deployment topology, reliability strategies, observability, performance bottlenecks, and measurable outcomes. Also cover what went well, what failed, and what you'd do differently.

“This is essentially 'design your own past work from scratch in front of us' and it's way harder than a made-up system design prompt because you can actually be wrong.”

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Uber·Software Engineer·Onsite - Multi Round

Jul 2026
Uber SWE interview covering a pretty solid mix of coding and design. The questions ranged from thread-safe systems to scheduling problems with some interesting follow-ups that pushed beyond the obvious answers.
  • Design and implement a thread-safe Rate Limiter, then extend it to handle multi-threading, and also a version where the current time is not passed in as a parameter.
  • Implement binary search from scratch without using any standard library functions.
  • Design a data structure with a getTopK method that returns the top K elements, using a doubly linked list as part of the approach.
  • Design a Meeting Scheduler that finds open time slots across multiple calendars. Follow-ups included applying MapReduce to the scheduling problem and ranking rooms using priority factors like usage count and meeting duration.

“The basic rate limiter wasn't bad but the follow-ups stacked up fast.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

Jul 2026
PM interview at Uber with a product sense question that blended personal preference with a real retention problem. Pretty standard format but the question had some teeth to it.
  • What's your favorite fitness product, and how would you diagnose and address a situation where users are consistently dropping off after about three months?

“The first part is basically a warmup but it sets a trap for the second part.”

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Uber·Software Engineer·Technical Phone Screen

Jul 2026
Uber SWE interview, technical phone screen, one coding question the whole time. Pretty focused session, no fluff.
  • Implement Promise.all() from scratch in JavaScript.

“I've seen this question floating around so I wasn't totally blindsided, but actually writing it cleanly under pressure is a different story.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jul 2026
Uber system design round for a software engineering role. The question was about taking a working cycle detection algorithm and thinking through everything that would need to change before it could actually live in production. Broader than I expected.
  • You've implemented cycle detection on a directed dependency graph of services. How would you harden and improve this component for real production use, covering things like readability, performance at scale, error handling, observability, testing, API design, and extensibility?

“This was deceptively open-ended.”

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Uber·Data Scientist·Technical Phone Screen

Jul 2026
Uber data science interview with a single brutally deep question on experiment design for a two-sided marketplace. The whole thing was essentially one extended case study that kept branching into sub-problems. Dense.
  • Uber is launching a new networked product in a two-sided marketplace with riders and drivers. Design a causal experiment that accounts for interference and network effects. Cover your unit of randomization and why, how you'd limit and measure spillovers, your primary and guardrail metrics, power calculations under clustering, bias-reduction techniques, SUTVA violation diagnostics, and how the design changes if driver supply is effectively unlimited. Walk through a concrete rollout and analysis plan.

“This question is basically seven questions duct-taped together.”

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Uber·Software Engineer·Onsite - System Design / Architecture

Jul 2026
Uber system design round for a software engineer role. The whole session was focused on one meaty data structure problem, and they really wanted you to go deep on the implementation details rather than just sketch a high-level architecture.
  • Design an in-memory data structure that supports adding items, incrementing or decrementing their frequency (with deletion at zero), and returning the top K items by frequency, where ties are broken by most recent update. Updates should be O(1) amortized and retrieval O(k).

“This one took me a while to even understand what they were asking.”

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Uber·Data Scientist·Technical Phone Screen

Jul 2026
Uber Data Scientist technical screen, pretty much one meaty coding problem with a couple of follow-ups tacked on. The core question was algorithmic but had enough real-world flavor to keep it interesting. Left feeling okay about it but not sure I handled the streaming follow-up well.
  • Given n trip intervals [start, end) in seconds representing when rides are active, write a function that returns the maximum number of trips happening at the same time, plus one timestamp when that peak occurs. Half-open intervals mean a trip ending at t and another starting at t do NOT overlap. Aim for O(n log n) time and O(1) extra space.
  • Extend the solution to also return the smallest contiguous time range [L, R) during which the maximum concurrency holds without dropping.
  • How would your approach change if the trip intervals arrive as a stream and you can't store all of them at once?

“I went with the classic event-based sweep: split each interval into a +1 at start and -1 at end, sort the events, then scan.”

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