Uber Interview Questions

Uber Coding & Algorithms Interview Questions

Practice 303 real Uber interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Machine Learning, Behavioral & Leadership, Statistics & Math — across Software Engineer, Data Scientist, Machine Learning Engineer, and Technical Program Manager roles. Real questions from actual interviews with detailed solutions, focused guidance, and concrete interview preparation so you can practice the exact problem types Uber asks. Expect a coding-heavy loop for software engineering candidates: timed algorithm problems, online-assessment style OAs, and system-design tasks. For Software Engineer roles the recurring technical themes here are algorithm puzzles (kth-smallest-in-BST, knight/grid and reversal problems, prime-ending path counts), OA-style coding questions, and product-oriented design prompts such as a pickup-area driver queue and global nearby-restaurant search. Data Scientist questions center on membership/discount experiments, cold-start restaurant ratings and their launch evaluation, driver-acceptance modeling, and marketplace-impact analyses. Machine Learning Engineer prompts focus on completion-rate gaps, implementing attention and regression models, feed-ranking and restaurant-recommendation design, and pickup-location optimization. TPM items emphasize delivery-address fixes, competitive product comparisons, and leadership stories. Prepare by timing practice coding, rehearsing marketplace case studies, building short model write-ups, and polishing STAR examples for behavioral rounds.

303 Questions 1 Company07.03.2026
Showing 20 results
Role
Uber logo
Uber
Medium
Software EngineerIntern

Last Truck to Leave a One-Dimensional Lane

Last Truck to Leave a One-Dimensional Lane Implement last_exit_time(lane_length, positions, velocities). Distinct trucks start at integer positions st...

Coding & Algorithms
24
0
421 people solved
Jul 3, 2026
Uber logo
Uber
Medium
Software EngineerIntern

Kth Employee Reached in an Ordered Hierarchy

Kth Employee Reached in an Ordered Hierarchy Implement kth_recipients(boss, queries). Employees are numbered 0 through n - 1. boss[0] == -1; for every...

Coding & Algorithms
11
0
154 people solved
Jul 3, 2026
Uber logo
Uber
Medium
Software EngineerIntern

Minimum Delivery Cost Between Cities

Minimum Delivery Cost Between Cities Implement minimum_delivery_costs(delivery_charges, queries). There are n cities indexed from 0 to n - 1, and city...

Coding & Algorithms
15
1
124 people solved
Jul 3, 2026
Uber logo
Uber
Medium
Software EngineerSenior+

Design a Ride-Sharing System (Uber-style Core Platform)

Design a Ride-Sharing System (Uber-style Core Platform) Design the core backend of a ride-sharing platform like Uber. Riders open the app, see nearby ...

System Design
6
0
88 people solved
Jun 28, 2026
Uber logo
Uber
Hard
Software Engineer

Design a Real-Time Top-K Ranking System

Design an object-oriented, real-time Top-K ranking system. The system continuously receives score updates for a large set of entities — for example us...

Software Engineering Fundamentals
415
2
5433 people solved
May 2, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design a Food-Delivery Backend (Uber Eats-style)

This system design question tests a candidate's ability to architect a large-scale, multi-actor backend involving geospatial matching, real-time data ...

System Design
27
0
282 people solved
Jun 23, 2026
Uber logo
Uber
Medium
Software EngineerSenior+ Locked

Design a Real-Time Chat System

This system design question tests a candidate's ability to architect a scalable real-time messaging platform, focusing on transport protocol selection...

System Design
9
0
83 people solved
Jun 19, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design a Food Delivery Cart

This question evaluates competency in designing stateful, user-facing subsystems including data modeling, API design, session persistence, caching, co...

System Design
186
1
1402 people solved
Apr 21, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design a Distributed Logging System

This question evaluates a candidate's ability to architect a large-scale distributed logging system, testing competency in data ingestion pipelines, f...

System Design
25
0
220 people solved
Jun 8, 2026
Uber logo
Uber
Medium
Software EngineerSenior+

Bar Raiser: Architecture Depth, Technical Influence & Ownership

Bar Raiser: Architecture Depth, Technical Influence & Ownership This is a senior-level Bar Raiser interview that blends behavioral signal with archite...

Behavioral & Leadership
6
0
57 people solved
Jun 28, 2026
Uber logo
Uber
Medium
Software Engineer AI Locked

Design a Parking Lot

This question evaluates object-oriented modeling, API design, resource allocation, and concurrency control by asking for classes, relationships, key m...

Software Engineering Fundamentals
78
0
754 people solved
Apr 21, 2026
Uber logo
Uber
Medium
Data ScientistNew Grad Locked

Design Uber Eats Restaurant Recommendations

This question evaluates a candidate's ability in end-to-end machine learning system design for personalized restaurant recommendations in a food-deliv...

ML System Design
26
0
207 people solved
Apr 30, 2026
Uber logo
Uber
Medium
Machine Learning Engineer

Implement CLIP Contrastive Loss

Given a minibatch of paired image and text embeddings, implement the symmetric contrastive loss used in CLIP-style image-text representation learning....

Machine Learning
15
0
132 people solved
Apr 3, 2026
Uber logo
Uber
Medium
Software EngineerSenior+

Solve stock profit and vertical tree traversal

You have a 60-minute coding interview with two algorithm questions: 1) Max profit from one stock trade - Input: an integer array prices, where prices[...

Coding & Algorithms
13
0
133 people solved
Feb 9, 2026
Uber logo
Uber
Medium
Software EngineerSenior+ Locked

Shortest Path in a Grid with Blocked Cells

This question tests a candidate's practical grasp of graph traversal algorithms applied to 2D grid problems, specifically BFS for unweighted shortest-...

Coding & Algorithms
0
0
9 people solved
Jun 19, 2026
Uber logo
Uber
Medium
Software Engineer

Design a Parking Garage Object Model

Design an object-oriented model for a multi-level parking garage. The garage should support: - Multiple floors and parking spots. - Different vehicle ...

Software Engineering Fundamentals
18
0
130 people solved
Apr 12, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design an Uber Eats Cart Service

This question evaluates a candidate's ability to design a distributed shopping-cart service for a food-delivery platform, testing competencies in syst...

System Design
68
0
462 people solved
May 7, 2026
Uber logo
Uber
Medium
Machine Learning EngineerSenior+

Present a Marketplace ML Project Deep Dive

In a Machine Learning Engineer interview for a pricing, marketplace, or growth team, present a recent representative ML project. Your deep dive should...

ML System Design
5
0
78 people solved
Apr 19, 2026
Uber logo
Uber
Medium
Software Engineer Locked

Design a Stock Trading Platform

This question evaluates a candidate's ability to design a robust, scalable brokerage platform covering distributed systems architecture, transactional...

System Design
10
0
133 people solved
May 11, 2026
Uber logo
Uber
Medium
Software Engineer

Design Product Page View Tracking

Design a view-tracking system for a large e-commerce product detail page. When a shopper opens a product page on web or mobile, the system should reco...

System Design
10
0
107 people solved
Apr 12, 2026

Frequently Asked Questions

How hard are Uber interview questions?
Uber interview questions range from moderate to very challenging depending on role and level. Software Engineer loops emphasize data structures, algorithms and system-design problems that often require multi-step solutions and production tradeoffs, so expect mid-to-hard coding and design tasks. Data Scientist interviews skew toward analytics, experimentation and marketplace judgment with case-style product questions that reward rigorous causal thinking. Machine Learning Engineer rounds mix implementation and ML-system design, and TPM questions focus on program delivery and stakeholder tradeoffs. Preparation quality and interview level (junior vs senior) are the main determinants of perceived difficulty.
What is Uber's interview process and which roles ask these question types?
The typical Uber hiring sequence starts with a recruiter screen, followed by one or two technical phone or take-home assessments for some roles, then an onsite or virtual loop of four to six interviews and a hiring-committee review. Software Engineer rounds concentrate on coding, online assessment problems and system design. Data Scientist interviews emphasize SQL, experiments, product-analytics cases and behavioral ownership. Machine Learning Engineer interviews add ML model implementation and productionization questions. Technical Program Manager interviews focus on cross-functional program examples and behavioral leadership. Timelines usually span three to six weeks.
How long should I prepare for an Uber interview and how should I structure my timeline?
Plan your preparation based on role and current skill level. For Software Engineer positions allocate six to twelve weeks focusing on timed coding practice, mock interviews and system-design case work. Data Scientist candidates should budget three to six weeks prioritizing SQL, experimentation, product-case practice and clear storytelling about impact. Machine Learning Engineers need four to eight weeks combining model implementation, systems design and coding. TPM candidates can prepare in two to four weeks concentrating on program examples and stakeholder communication. Include final-week full mock loops and a review of role-specific Uber product scenarios.
Which specific subtopics should I focus on for each position at Uber?
For Software Engineers concentrate on algorithmic patterns seen in past Uber questions: BST kth-smallest, graph and knight problems, two online-assessment algorithm tasks, queue design for pickup-area driver matching, and product-oriented designs like global nearby-restaurant search and trade-off-driven design changes. Data Scientists should drill A/B testing, causal inference, cold-start rating models, marketplace evaluation (driver acceptance, membership and priority delivery impact) and translating analyses into action. Machine Learning Engineers should practice implementing attention, linear and logistic regression, feed ranking and ML-system tradeoffs including pickup-location optimization. TPMs should rehearse unclear-address resolution and cross-product comparisons with crisp ownership stories.
What standout tips and common pitfalls should I know before interviewing at Uber?
Standout tips: always clarify requirements and constraints up front, structure answers around measurable metrics and business impact, and narrate tradeoffs between latency, cost and accuracy. Use concrete examples from marketplace contexts and quantify outcomes when possible. For coding, write clean, testable code and discuss complexity and edge cases. Common pitfalls include skipping assumptions, failing to justify metric choices in product/analytics problems, neglecting production implications for ML designs, and overfitting to toy solutions instead of addressing scale and reliability. End with clear next steps or monitoring plans to show ownership.

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