Jobs
About the Role
We are seeking a Sr. Staff Engineer and Tech Lead to join Uber's Mobility Matching & Segmentation organization. You will play a central role in architecting and evolving the ML-powered systems that determine how riders are matched with drivers in real-time and how marketplace segmentation enables differentiated products like Wait & Save, Predictive Dispatch, and XShare. You will tackle some of the most complex optimization and systems problems at Uber, working at the intersection of machine learning, distributed systems, and real-time decision-making - with your contributions directly impacting the experience of millions of users worldwide.
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What the Candidate Will Do
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Be the Tech Lead for a complex domain within Matching & Segmentation, setting technical direction and driving architecture decisions across matching algorithms, segmentation models, forecasting systems, and real-time marketplace infrastructure.
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Design, develop, and deploy ML and optimization systems that solve high-impact business problems at scale - including real-time matching, reinforcement learning-based dispatch, and experiment-driven product development.
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Lead projects that span across orgs (e.g., matching, driver pricing, rider pricing, surge, platform) with significant cross-org dependencies and design complexity.
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Collaborate closely with Scientists, Product Managers, and peer engineering teams to define technical strategy, translate business requirements into system designs, and deliver high-quality solutions.
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Drive ongoing improvements in system reliability, performance, scalability, and efficiency through strong engineering practices, automation, and observability.
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Mentor and grow engineers across the organization, including Senior and Staff engineers, raising the technical bar and fostering a culture of engineering excellence.
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Contribute to the design and evolution of Uber's large-scale experimentation infrastructure, including Switchback experiments that power marketplace optimization decisions.
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Deliver and review technical designs, code, and documentation to a high standard, and champion best practices in data management, data quality, and service deployment.
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Basic Qualifications
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Bachelor's degree in Computer Science, Computer Engineering, or a related technical field.
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8-10+ years of professional software development experience, building and operating systems in production environments.
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Strong knowledge of backend development, distributed systems, and system design for large-scale, low-latency applications.
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Experience with ML systems, optimization algorithms, or real-time decision systems in production.
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Demonstrated ability to lead complex, multi-team technical initiatives with significant cross-org dependencies.
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Excellent communication skills and the ability to collaborate effectively with cross-functional teams including Product, Science, and Operations.
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Proven ability to mentor and elevate other engineers, including Senior and Staff-level ICs.
Preferred Qualifications:
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MS or PhD in Computer Science or a related field.
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Deep experience with marketplace systems, matching/ranking algorithms, reinforcement learning, or forecasting systems.
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Experience designing and running large-scale online experiments (e.g., Switchback, A/B testing frameworks).
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Proficiency in languages such as Go, Java, or Python, with strong foundations in performance optimization and debugging across complex stacks.
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Strong analytical and problem-solving skills with comfort navigating ambiguous, high-impact problem spaces.
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Track record of driving both technical innovation and raising organizational engineering standards.
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For San Francisco, CA-based roles: The base salary range for this role is USD**$267,000 per year**
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USD**$297,000 per year**.
You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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