Katkat

Company

Uber interview questions

217 practice questions in the style of Uber's interviews, covering Behavioral & Leadership, Statistics & Math, Coding & Algorithms, Machine Learning, System Design, Data Manipulation (SQL/Python), Analytics & Experimentation, Software Engineering Fundamentals, ML System Design, Product / Decision Making, Product Design & Strategy.

Questions217

9 easy156 medium52 hard

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Uber interview questions by the numbers

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Katkat has 217 Uber interview questions. The largest topics are Coding & Algorithms (53%), System Design (12%) and Analytics & Experimentation (10%). By difficulty: 4% easy, 72% medium and 24% hard. The most common round is Technical Screen (47%). Frequent concepts include System Design, Algorithms, Greedy and Data Structures.

Difficulty

  • Easy4% · 9
  • Medium72% · 156
  • Hard24% · 52

Interview rounds

  • Technical Screen47% · 102
  • Onsite41% · 88
  • Online Assessment12% · 26
  • Other0% · 1

Roles

  • Software Engineer63% · 137
  • Data Scientist25% · 54
  • Machine Learning Engineer10% · 21
  • Frontend Engineer1% · 2
  • Backend Engineer0% · 1

Frequent concepts

  • System Design6% · 13
  • Algorithms5% · 11
  • Greedy5% · 11
  • Data Structures5% · 10
  • Causal Inference4% · 9
  • Distributed Systems4% · 9

Showing 181–210 of 217 results

  • An object-oriented design interview question asking you to model a parking lot and implement working check-in and check-out methods. It tests class design and relationships, fast free-spot lookup across vehicle sizes, ticket handling, fees, edge cases, and thread safety.

    UberSoftware EngineerSoftware Engineering FundamentalsOnsite
  • This question evaluates a developer's ability to design and implement a robust parser and evaluator for a parenthesized expression language, testing parsing, lexical scoping and variable binding, operator semantics, error detection, and safe integer arithmetic.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates a candidate's competence in end-to-end ML system design, product-oriented machine learning, and cross-functional skills such as feature engineering, model deployment, online experimentation, monitoring, stakeholder communication, and measuring business impact.

    UberMachine Learning EngineerML System DesignTechnical Screen
  • This question evaluates proficiency with representing and traversing hierarchical directory trees and producing depth-based formatted output, testing concepts such as tree traversal, recursion or iterative depth tracking, and string formatting for indentation.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to design a real-time room allocation and ranking service in the System Design domain, testing competencies in architectural design, ranking and scoring functions, data sourcing and freshness, fairness mechanisms, and online evaluation and experimentation.

    UberSoftware EngineerSystem DesignOnsite
  • This question evaluates proficiency in graph algorithms and dependency resolution, including concepts such as topological ordering, cycle detection, and complexity analysis, plus systems-level reasoning about service deployment dependencies.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the implementation of a spatial indexing structure by requiring the construction of a Point Quadtree that recursively divides 2D space into four quadrants.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This question tests the ability to model partial ordering constraints using a directed graph and perform a topological sort to deduce a valid sequence.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to perform a multi-source shortest path search on a grid to determine the influence of characters on empty spaces, using Manhattan distance and lexicographical tie-breaking.

    UberBackend EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's skills in dependency resolution, graph traversal and cycle detection while reasoning about an externally discovered dependency subgraph and ordering constraints.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Maintain the earliest single-visit ID with counts and queue pruning, handling permanent duplicates, empty results, and strict versus amortized constant-time queries.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A grid pathfinding problem in which a robot travels from a start cell to a destination through open, blocked and charging cells, spending one battery unit per move and refilling at chargers. The best route is ranked by fewest charging stops, then smallest required battery capacity, then fewest moves.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage dynamic intervals and determine if a new meeting can be scheduled without overlapping existing appointments using efficient data structures.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to model a 2D grid as a graph and implement a Breadth-First Search (BFS) to find the shortest path between two points while respecting obstacles.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a controlled experiment for a two-sided marketplace and evaluate whether a discount-doubling strategy is statistically and economically viable.

    UberData ScientistStatistics & MathTechnical Screen
  • This question tests the ability to implement a single-elimination tournament simulation using queue-based structures and demonstrates competency in designing a relational database schema for tournament record-keeping.

    UberFrontend EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to implement grid-based simulation and pattern-matching algorithms, including handling fixed-shape placements, internal holes, bounds checking, collision detection, and explicit scanning/tie-breaking rules.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Simulate robot on grid with obstacles evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • Given a positive integer of up to 18 digits as a string, return the smallest palindromic number strictly greater than it, or the input itself when no such palindrome stays within 18 digits. Tests digit-level reasoning and edge cases such as palindromic inputs, carries and changes in digit count.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This multi-problem set evaluates broad algorithmic problem-solving skills, including bitwise reasoning, sliding-window and frequency analysis, stack/monotonic patterns, graph/DP reasoning with constrained jumps, and tree-path parity techniques.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This collection evaluates understanding of search techniques (binary search and BFS), graph and grid traversal, state-space shortest-path reasoning, randomized placement with adjacency counting, and attention to implementation quality and complexity trade-offs.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • This two-part prompt evaluates array and permutation reasoning for detecting contiguous value ranges and directed graph/tree reasoning for minimizing edge reversals when choosing a root, testing competencies in index and interval management, graph traversal and orientation, and algorithmic counting.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates graph modeling, state-space exploration, and shortest-path/reachability reasoning for nonstandard movement rules and constrained state transformations.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates algorithmic problem-solving skills in constrained path optimization and resource-allocation throughput maximization, including concepts such as graph modelling with prime-step constraints, dynamic programming, number-theoretic reasoning, and combinatorial optimization.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to optimize resource allocation using a greedy approach with a priority queue and to determine graph reachability within a constrained network.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to optimize string transformations using bitmask dynamic programming and to perform efficient range-based queries on a grid using a 2D data structure or sweep-line approach.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests dynamic programming with array constraints and tree-based traversal combined with bitwise parity checks for palindromic properties.

    UberSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Assesses proficiency in array processing and binary tree traversal algorithms—specifically single-pass analysis of time-series data and coordinate-based vertical ordering of tree nodes; Category: Coding & Algorithms; Level of abstraction: implementation-level algorithmic coding.

    UberSoftware EngineerCoding & AlgorithmsOnsite
  • These two problems evaluate algorithmic problem-solving skills: the first focuses on spatial reasoning and grid-based distance computation relative to obstacles, while the second targets tree traversal and character-frequency reasoning for ancestor-path palindrome checks.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Construct any legal adjacent-swap sequence that sorts a numbered matrix into snake order, prove correctness, validate the output, and discuss reducing swap counts.

    UberSoftware EngineerCoding & AlgorithmsTechnical Screen

Uber interview experiences

All 42 →
  • Building a Directory Tree and Traversing It with a Manual StackUber · Software Engineer · Technical Screen · Sep 2026
    Rejected

    The interview lasted 45 minutes. We first went through my resume. I was asked about my most challenging project and the technology stack I normally use, and the interviewer introduced the work of the hiring group. The remaining half hour was for coding. Given a series of file paths, I needed to build a directory tree and find the full path of a file in that tree. Directory names could repeat, but…

  • Matrix Swaps and Infrastructure DesignUber · Software Engineer · Senior+ · Onsite · Sep 2026

    The author describes an Uber infrastructure-backend interview process with a phone screen and three virtual-onsite rounds. The screen asked for a valid sequence of adjacent swaps that arranges a matrix into alternating-direction sorted rows, followed by discussion of reducing the number of operations. The applicant had to create tests and found the time limit demanding. Onsite coding involved rep…

  • 45 Min Coding Plus 15 Min Free-Form ML Design, Onsite Invite Next DayUber · Machine Learning Engineer · Technical Screen · Aug 2026
    In progress

    The phone screen format was 45 min coding + 15 min design. For coding I got the high-frequency "find robot" problem. I discussed the brute force solution with the interviewer, then how to precompute the distances in all four directions to speed it up, and finally wrote the optimized version. The interviewer didn't provide any test cases in HackerRank and didn't ask me to write any either. I only…

  • A Three-Level Robot Path OptimizationUber · Software Engineer · Senior+ · Technical Screen · Aug 2026

    In a grid, a robot needs to move from a starting point to a destination. Each move consumes one unit of battery power. Charging cells are distributed throughout the grid, and when the robot reaches one, its battery is recharged to full. The task is to find an optimal path using the following priorities, compared lexicographically: Minimize the number of charging cells used. Minimize the maximum b…

  • Four Onsite Rounds, All About the Follow-UpsUber · Software Engineer · Onsite · Aug 2026

    Four rounds, questions weren't hard but the pace was really fast Let me lead with the conclusion: Uber's problems really aren't hard, but they move fast. 45 minutes a round, and the interviewer practically wants you to knock out the main problem in 15 minutes so there's a full half hour left for piling on requirements. It felt less like solving problems and more like sitting in a requirements rev…

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