Uber Software Engineer candidates report an online assessment, a recruiter screen, live coding, and in later loops, hiring-manager, system design, database and behavioral rounds. Algorithms carry heavy weight.
$199K
Avg. Base Comp
$355K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe Uber's Software Engineer interviews as algorithm-heavy early, with design depth mattering more in later loops. Several report an online assessment of three or four LeetCode-style problems, ranging from easy or medium up to hard. One mentions a two-hour limit and an expectation of clean complexity analysis. Reported coding topics include linked lists, strings and arrays, and a 2D matrix problem. Others include a minimum-cost path with teleportations, a grid of restaurants where you count delivery zones formed by adjacent restaurants, and an escape-room problem about the largest group whose size preferences can all be met. One candidate says a live problem was a modified medium rather than a familiar one, so memorized templates may not be enough. Time pressure comes up too: one candidate spent about 25 minutes chatting and then had only around 20 minutes to code.
Live coding formats vary. One candidate worked on CodeSignal, had to work out the expected output from the input, and ran the code at the end. That candidate was walked through the format in a meeting beforehand. Practice writing complete, runnable code while narrating your reasoning.
The candidate who accepted an offer described a hiring-manager round mixing product sense with OOP-style coding in Python or Java. Next came a five-round onsite covering data structures, database lifecycles and SQL, deep system design on a real-time gaming leaderboard, and behavioral questions. Another candidate heard a ride-hailing platform described as a design prompt. Be ready to defend architecture, APIs and data flow.
Behavioral questions cover ownership, handling feedback, past architectural decisions and why you want to join Uber. Most candidates in these reports did not receive an offer, so treat each round as a real filter.
Synthesized from 67 candidate reports by our editorial team.
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Real interview reports from people who went through the Uber process.
What stood out most about Uber's process was how transparent it was from the start. The interviewer did a good job laying out every stage at the beginning, and all of my interviews were scheduled up front rather than trickling in one at a time. The loop started with a resume screen, then moved into two DSA coding rounds, a system design round, and a cultural fit interview. Each stage felt distinct, so I always knew what kind of signal they were trying to get from me.
The ending was also more structured than I expected. Instead of getting a bare yes or no, they combined the results from every round into one overall assessment and shared it with me on a feedback call. I didn't get an offer. Because the final decision was based on the combined picture, I'd recommend treating the whole loop as a single evaluation and preparing for every round with equal care.
Prep tip from this candidate
Since Uber combines the results of every round into one overall assessment, prepare for the two DSA rounds, system design, and cultural fit with equal seriousness rather than over-investing in one. Expect all rounds to be scheduled together, so plan your prep calendar around that compressed timeline.
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Topics based on recent interview experiences.
Featured question at Uber
Write a query to select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.
| Question | |
|---|---|
| Weighted Keys | |
| Top 3 Users | |
| Maximum Profit | |
| Download Facts | |
| Sum to N | |
| User Experience Percentage | |
| Distance Traveled | |
| Size of Joins | |
| P-value to a Layman | |
| Google Maps Improvement | |
| Third Purchase | |
| Groups of Anagrams | |
| Type-ahead Search | |
| Random Weighted Driver | |
| Sort Strings | |
| Binary Tree Conversion | |
| Hurdles In Data Projects | |
| Production Model Monitoring | |
| Dijkstra implementation | |
| Christmas Dinner Ingredient Optimization | |
| RAG Strict Source Control | |
| Messenger Service Design | |
| KNN From Scratch | |
| Type I and II Errors | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Max Width | |
| Uniform Car Maker | |
| The Pirate’s Hunt | |
| Triangle as Binary Array |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report a recruiter or HR call, in one case about 15 minutes. It typically covers background, motivation and past experience. One candidate also got a basic question on the difference between a list and a set and was asked about an important architectural decision, so prepare a concise project story.
Several candidates report an online assessment with three or four problems, ranging from easy to hard, and one mentions a two-hour limit. Reported topics include strings, arrays, handling large input line by line, and dynamic programming. One candidate never heard back after the assessment, so aim for complete working solutions.
Candidates report live coding with engineers, sometimes in a one-hour slot or on CodeSignal. Reported problems include linked lists, a 2D matrix, a minimum-cost path with teleportations, a restaurant grid with connected delivery zones, and modified medium problems. Interviewers may expect you to explain your reasoning, handle edge cases and run working code.
One candidate describes a hiring-manager round mixing product sense and execution, with OOP-style coding in Python or Java and some higher-level design. Another reports a final in-depth coding interview with the manager. Prepare a concise project story and be ready to discuss tradeoffs.
One candidate reports an onsite of five back-to-back rounds. These covered data structures, database lifecycles and SQL, system design for a real-time leaderboard, and behavioral questions on ownership and feedback. A ride-hailing platform was also described as a design prompt. The mix likely varies by level and team, so confirm it with your recruiter.
