← Back to Directory

Uber interview notes, page 34 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 - System Design / Architecture

May 2026
Uber system design round for a software engineer role. One question, stock trading system, and it was a pretty involved session.
  • Design a stock trading system.

“Spent the first few minutes just trying to scope it down because stock trading can mean a hundred different things.”

View Post

Uber·Data Scientist·Onsite - Behavioral / Leadership

May 2026
Uber data scientist interview with a heavy focus on navigating ambiguity and cross-team chaos. The questions were layered and scenario-driven, not the usual 'tell me about a challenge' stuff. Felt more like a case study than a behavioral round.
  • Why Uber and why are you making this career move now? Connect your answer to the company's mission, the metrics you'd own, and the specific domain challenges you'd be stepping into.
  • Walk me through a project with high ambiguity and cross-team dependencies. What was the goal, how did you get involved, who were the stakeholders, and what made it genuinely hard?
  • Midway through your project, a critical incident forces an urgent deliverable within 48 hours while you still have three other active workstreams. How do you prioritize across all four, and what do you explicitly cut, defer, or run in parallel? How do you communicate the tradeoffs and get buy-in?
  • Tell me about a disagreement with a key stakeholder over methodology or scope. How did you surface the underlying assumptions, build your case, and eventually influence the outcome without having direct authority?
  • Reflecting on that project, what would you do differently, and how would you actually institutionalize those lessons so they don't just stay in your head?

“This is the kind of question where a vague answer kills you fast.”

View Post

Uber·Software Engineer·Technical Phone Screen

May 2026
Uber SWE interview with a classic sliding window design problem. The question itself was clean but the follow-up about scale is where things get interesting and where I felt a bit underprepared.
  • Design a hit counter that tracks the number of hits received in the past 300 seconds. It should support a hit(timestamp) method and a getHits(timestamp) method. Timestamps are monotonically increasing and multiple hits can share a timestamp. Follow-up: how does your design hold up if hits per second can be extremely large?

“My first pass was a queue, just append timestamps on hit() and prune anything older than 300 seconds on getHits().”

View Post

Uber·Software Engineer·Onsite - System Design / Architecture

May 2026
Uber system design round for a software engineering role. The problem was a referral tracking system with subtree aggregation, which sounds manageable until you actually have to talk through the scaling part under pressure.
  • Design a system to track customers and their referral chains, where each customer has their own revenue and an optional referrer. Support inserting new customers and querying the k customers whose total subtree revenue meets a minimum threshold, sorted ascending.

“The tree structure part clicked pretty fast for me, parent pointers, store subtree sums, update ancestors on insert.”

View Post

Uber·Software Engineer·Onsite - Coding / Algorithms

May 2026
Uber onsite coding round for SWE, one question the whole time: design and implement a random Bingo card generator with some tricky constraints around rows and columns. Not your typical leetcode grind, more of a design-your-way-through-it problem.
  • Design and implement a random 3x9 Bingo board generator where each row has exactly 5 numbers and 4 blanks, each column is restricted to a specific decade range (e.g. column 0 holds 1-10, column 1 holds 11-20, etc.), and cells are filled probabilistically while keeping all row and column constraints satisfiable throughout the process.

“The part that got me was the feasibility check.”

View Post

Uber·Software Engineer·Onsite - System Design / Architecture

May 2026
Uber system design round for a software engineer role. The problem was a custom customer-revenue tracking system with some tricky query semantics, and most of the time went into debating data structures and their tradeoffs.
  • Design a customer-revenue system with three operations: add a new customer with a starting revenue and return their id; add a customer via referral where the referrer's revenue also gets bumped by the new customer's revenue; and query the k customers with the smallest revenues among those strictly above a given threshold. Discuss suitable data structures and the complexity of each operation.

“The add operations are straightforward enough but the referral one trips you up because updating the referrer's revenue means their position in any sorted structure changes.”

View Post

Uber·Software Engineer·Online Assessment (OA)

May 2026
Uber's Hack2Hire OA was a 90-minute two-problem set and the one I got tripped up on was a Jump Game variant with a pretty specific twist on allowed step sizes. Not a brutal interview format but the hidden test cases are where people get burned.
  • Given an integer array, start at index 0 and reach the last index by jumping either +1 or +k steps where k is a prime number whose last digit is 3 (like 3, 13, 23, 43...). Maximize the sum of values at all landed indices.

“My first instinct was just brute force DP, loop over every valid jump from each position.”

View Post

Uber·Software Engineer·Technical Phone Screen

May 2026
Uber coding screen with a pretty gnarly optimization problem involving pipeline throughput and budget constraints. Not a typical LeetCode grind question, felt more like a resource allocation puzzle with a twist.
  • You have a chain of services where each feeds into the next. Each service can be scaled up multiple times, and each scale-up has a throughput gain and a cost. Given a total budget, how do you choose which scale-ups to apply so that the end-to-end pipeline throughput (bottlenecked by the weakest service) is maximized?

“The bottleneck part is what trips you up first.”

View Post

Uber·Machine Learning Engineer·Technical Phone Screen

May 2026
First round at Uber for an MLE role. It was a project deep dive and things went sideways pretty fast once I realized my project wasn't really what the team was looking for.
  • Walk me through a recent project you worked on that you feel represents your work well.

“I went with a GenAI agent project because I thought it showed breadth: business context, system design, data pipeline, eval, post-launch tradeoffs.”

View Post

Uber·Software Engineer·Technical Phone Screen

Jun 2026
Uber system design interview, one question about the ride request flow. Pretty thin on details but the core question was interesting enough to think through.
  • Walk me through what happens technically when a user requests a ride on Uber. Is there anything that can be pre-processed or cached ahead of time to make the system faster?

“This is a meaty one.”

View Post