
Uber Software Engineer candidates report coding-heavy assessments and live rounds, with design and behavioral discussions becoming more prominent in senior loops. Prepare to explain solutions, tradeoffs, and past work clearly.
$203K
Avg. Base Comp
$453K
Avg. Total Comp
4-6 rounds
Typical Rounds
2 months
Process Length
Uber Software Engineer interviews described by candidates center on algorithmic problem solving, but the mix changes with level and team. Several candidates reported an online assessment or early coding screen with LeetCode-style questions. Reported examples include dynamic programming, binary search, trees, recursion, string manipulation, discounts, and an optimization problem involving travel time and changing energy. A correct initial solution may lead to follow-up extensions, so narrating assumptions, edge cases, complexity, and possible optimizations matters alongside reaching working code.
The reported structures varied. One candidate described four rounds: an assessment, two technical interviews, and a hiring-manager round. Another described a phone screen, a separate live-coding interview, and a four-round business loop covering coding, architecture, and behavioral topics. The difficulty could also rise after the early screen, so do not assume an approachable first round represents the full loop.
For experienced candidates, reports add low-level design, architecture, service design, and project discussion. Examples included designing or implementing a key-value store and discussing an Uber Eats cart service. Prepare to explain class and interface choices, component interactions, extensibility, and the reasoning behind a substantial past project.
Candidates explicitly reported end-to-end processes of about eight weeks or roughly two months. Some candidates who cleared the interviews then entered team matching, where open headcount and domain fit affected whether placement could proceed.
Synthesized from 27 candidate reports by our editorial team.
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Real interview reports from people who went through the Uber process.
The coding interview was the point where my process ended. I first had a recruiter screening call, where I was asked about the most challenging thing I had built in my career, and I was given study links before moving on. The coding round itself felt fair, but I was under enough pressure that my solution only ran partially, and I was rejected afterward.
The broader process seemed to put real weight on the assessment. The online assessment format included three LeetCode-style easy problems plus a much harder trie problem in a Codeforces-style setting. I also found the interviewers friendly and the job description clear. The team was very senior and involved in the evaluation, although each recruiter seemed to have a distinct interviewing style rather than following the stated topic plan rigidly. They spent a lot of time probing how I approached the assessment, not just the final answer.
My main takeaway is to make sure you can get a complete, working solution in the coding round before optimizing or adding extras. Be ready to explain your assessment approach and to discuss a substantial project from your career clearly. I did not receive an offer.
Prep tip from this candidate
Practice completing Codeforces-style problems under time pressure, especially trie problems, and be prepared to explain your reasoning and assessment approach in detail. Have a clear story about the most challenging project you have built.
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Sourced from candidate reports and verified by our team.
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 | |
| User Experience Percentage | |
| Sum to N | |
| Distance Traveled | |
| P-value to a Layman | |
| Google Maps Improvement | |
| Third Purchase | |
| Type-ahead Search | |
| Sort Strings | |
| Random Weighted Driver | |
| Hurdles In Data Projects | |
| Dijkstra implementation | |
| Christmas Dinner Ingredient Optimization | |
| Type I and II Errors | |
| Production Model Monitoring | |
| Max Width | |
| Uniform Car Maker | |
| Drink Production Allocation | |
| Uber Eats Customer Experience | |
| External Sorting | |
| Bernoulli Sample | |
| Client Solution Pushback | |
| Stakeholder Communication | |
| Two Cars | |
| k-Means from Scratch | |
| Your Strengths and Weaknesses |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report online assessments with two to four LeetCode-style questions, commonly described as medium to hard. Examples varied from graph and DP work to arrays, tries, and implementation-heavy problems; the exact question count and platform differed by account.
Candidates report brief recruiter conversations about background, motivation, and projects. Other accounts describe a business phone screen with an algorithmic question, so clarify with the recruiter whether the screen is logistical, technical, or split between both.
Several candidates report live coding on DSA topics such as graphs, trees, recursion, linked lists, and pathfinding. They describe follow-ups after an initial answer, making clear reasoning about complexity, edge cases, and optimization useful.
Senior and SDE-2 candidates report low-level design, architecture, or machine-coding discussions alongside conventional coding. Reported prompts included a key-value store, Splitwise-style implementation, and scalable systems; exact design depth may depend on level.
Candidates report hiring-manager or behavioral conversations about ownership, collaboration, conflicts, and past projects. Candidates who cleared a loop also reported team matching, where availability and domain fit could determine the next step rather than additional technical questions.