← Back to Directory

Uber interview notes, page 22 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·Onsite - Product Sense / Strategy

May 2026
Uber PM interview, just one question about UberPool. Short session but the question had a lot of surface area and I don't think I covered it well.
  • You're the PM for UberPool. How would you create value for it?

“I went straight to rider savings and driver utilization, which felt obvious in retrospect.”

View Post

Uber·Software Engineer·Technical Phone Screen

May 2026
Uber software engineer interview with a data structures problem centered on streaming IP hits. The follow-up about scaling to billions of records is where things got interesting and where I probably lost some points.
  • Design a component that processes a stream of server hit records (each containing an IP address) and supports two operations: recording a new hit from an IP, and returning the earliest IP that has appeared exactly once so far.
  • Follow-up: how would you scale this solution to handle millions or billions of hit records? Walk through memory usage, throughput, and the trade-offs between exact and approximate results.

“The core idea clicked pretty fast.”

View Post

Uber·Machine Learning Engineer·Technical Phone Screen

May 2026
Uber MLE interview with a product analytics case about alcohol orders in a food delivery marketplace. The question had three parts and went pretty deep into experimentation design, which I wasn't fully expecting for an MLE role.
  • In a food delivery marketplace, alcohol orders complete at a lower rate than non-alcohol orders. What are some plausible business or operational reasons for this gap?
  • What additional data would you look at to validate your hypotheses about why alcohol orders have lower completion rates?
  • The company runs a randomized experiment to improve alcohol order completion rates. Walk through how you'd evaluate the effect using a two-sample t-test, including the null and alternative hypotheses, assumptions, the test statistic, and how you'd interpret the result.

“I started with the obvious stuff like ID verification failures and age restrictions, then got into things like driver refusals and stricter delivery windows.”

View Post

Uber·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round for a security engineer role at Uber. Just one question but it took the whole conversation in a direction I wasn't expecting.
  • Tell me about a time you took ownership of work that wasn't explicitly assigned to you.

“I had a decent story ready but fumbled the delivery.”

View Post

Uber·Software Engineer·Onsite - System Design / Architecture

May 2026
Went through a system design round at Uber for a software engineering role. Just the one question, but it had enough surface area to keep me busy for the whole session.
  • Design a heatmap system.

“I jumped straight into the data ingestion layer and kind of forgot to nail down what kind of heatmap we were even talking about.”

View Post

Uber·Machine Learning Engineer·Technical Phone Screen

May 2026
Uber ML engineer interview that went deep into graph algorithms, which I was not fully expecting. The currency conversion problem sounds like a coding warmup but they kept pushing on the design and complexity until it turned into a full system design conversation.
  • Given a list of currency pairs and their conversion ratios, implement a function that returns the conversion rate between any two currencies, or -1 if no conversion path exists. Walk through your data structure choices and search algorithm, and analyze time and space complexity.
  • Follow-up: if currency conversions are directional and not necessarily reciprocal, how would you find the best possible conversion rate from a source currency to a destination? How do you model this as a weighted graph problem, and which shortest-path algorithm applies? Also address cycles and floating-point precision.

“I jumped straight to BFS on a directed graph, multiplying edge weights along the path.”

View Post

Uber·Software Engineer·Technical Phone Screen

May 2026
Uber coding interview with a graph problem that looks straightforward until you actually think about it. Reroot DP is the move but I didn't get there cleanly.
  • You're given a directed graph that forms a tree when you ignore edge directions. Find a root node such that the number of edge reversals needed to make all edges point away from it is minimized. Return that minimum count.

“I started with brute force, picked an arbitrary root, ran a DFS to count reversals, then tried to re-run for every possible root.”

View Post

Uber·Product Manager·Hiring Manager Screen

May 2026
Interviewed for a PM role at Uber, just the one question about impactful projects. Short and to the point, not much else to report.
  • Walk me through the project you're most proud of and why it mattered.

“Pretty standard opener but I still fumbled the 'why it mattered' part.”

View Post

Uber·Software Engineer·Technical Phone Screen

May 2026
Uber SWE interview with a tree-based string problem that looks like a graph question but really comes down to bit manipulation and palindrome parity. Solid problem, not a typical LeetCode grind.
  • Given an undirected tree rooted at node 0 where each node holds a lowercase character, for each query node count how many ancestors (including the node itself) form a sub-path whose characters can be rearranged into a palindrome.

“My first instinct was to just walk up the path and count character frequencies, which works but is way too slow if you think about the constraints.”

View Post

Uber·Software Engineer·Onsite - System Design / Architecture

May 2026
Uber data engineer interview with a system design question about building a rewards platform. Pretty open-ended, not a lot of constraints given upfront.
  • How would you design a rewarding system?

“I went straight into the data model and probably should've asked more clarifying questions first.”

View Post