About the role:
We're seeking an exceptional Staff Engineer to lead the marketplace simulation, control systems and data infrastructure powering Uber's millions rides daily. This role demands a proven track record of extraordinary technical leadership and innovative solutions at world-class technology companies.
You’ll architect and scale supply pricing simulation infrastructure and control systems processing terabytes of data daily, build the next generation of joint simulation systems spanning rider pricing, driver pricing, and matching, and design clean interfaces between supply pricing and broader marketplace optimization systems. You’ll also build supply pricing data foundation and optimize batch and streaming pipelines. This work directly impacts marketplace efficiency and offers a unique opportunity to tackle deep technical challenges across data, real-time optimization, distributed systems, and marketplace dynamics.
What the Candidate will do:
You’ll be working on infrastructure that directly affects millions of drivers’ livelihoods and riders’ experiences every day. Our pricing systems process billions of batch and real-time decisions, balancing marketplace efficiency, driver earnings, and rider satisfaction. You’ll have the opportunity to:
- Solve unique technical challenges at the intersection of batch and real-time optimization
- Build marketplace simulation infrastructure that powers one of the world’s largest marketplace platforms
- Work with cutting-edge pricing algorithms and ML systems that operate at unprecedented scale
- Shape the technical direction of critical business infrastructure with direct P&L impact
Technical Leadership & Architecture
- Architect simulation, optimization and control (PID controller) systems.
- Drive innovation in data infrastructure design, build a data foundation, improve data quality, and improve the efficiency of compute-intensive jobs.
- Design interfaces between driver pricing and other Marketplace optimization systems to ensure both accuracy and efficiency.
Cross-Functional Impact
- Collaborate with engineering teams across Marketplace to build a top-quality joint simulation framework, improve simulation accuracy, and improve algorithm iteration velocity.
- Partner with Data Science and Product teams to build a unified infrastructure supporting pricing algorithms and marketplace optimization
Engineering Excellence & Leadership
- Mentor senior engineers and grow technical leadership capability across the marketplace organization
- Establish engineering standards, team processes, architectural patterns, and operational excellence practices
Basic Qualifications:
Computer Science degree or equivalent technical education
8+ years building large-scale backend or platform systems at Staff/Principal scope.
Experience operating compute-intensive and data-intensive systems at scale, including capacity planning and cost efficiency in cloud environments
Strong data infrastructure background, experience in optimizing data foundation and pipeline efficiency.
Strong system design and algorithmic problem-solving skills
Experience partnering with Data Science / ML teams
Proven technical leadership across teams and org boundaries
- Drive architecture decisions across org boundaries
- Mentor senior engineers
- Set long-term technical direction and quality bar
Preferred Qualifications:
Background in pricing, ads, recommendations, or other areas involving optimization and control systems.
Hands-on experience designing or operating simulations and control systems
- Improving simulation accuracy
- Modernizing legacy simulation infrastructure with measurable improvements in accuracy, cost, or velocity
- Strong understanding of simulation evaluation, including simulation bias, feedback loops, and calibration techniques
Familiarity with optimization techniques (e.g., stochastic optimization, Monte Carlo methods, heuristic search) applied at scale
Exceptional technical craftsmanship with a passion for solving complex, real-world problems at massive scale
Marketplace mindset: Understanding of supply/demand dynamics and real-time optimization challenges
Innovation and ownership: Ability to identify breakthrough opportunities and drive them to completion
Data-driven decision making: Comfort with ambiguity and bias toward measurable impact
Collaborative leadership: Ability to influence across organizations and build consensus around technical direction
For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.
For all US locations, 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.