Staff Machine Learning Engineer - Mobility Verticals

About the Role
Uber is looking for an exceptional ML engineer to join our Mobility Marketplace Vertical team, where you'll tackle some of the most challenging problems in real-time marketplace optimization at unprecedented scale. You will develop and deploy sophisticated machine learning systems that power demand forecasting, supply/demand balancing, driver earnings prediction, and matching algorithms across our specialized mobility products: Airport, Reserve, and Rideshare.
Our systems operate at massive scale, processing 1M+ predictions/second and powering billions of rides globally. The work you do will directly impact millions of riders and drivers daily, ensuring optimal marketplace efficiency whether someone is catching a flight at JFK, scheduling a ride for tomorrow morning, or sharing their commute with other passengers. You'll be working on cutting-edge problems at the intersection of machine learning, operations research, and marketplace economics-building models that need to be both highly accurate and blazingly fast, balancing multiple objectives like rider wait times, driver earnings, and overall marketplace health.
This is a high-impact, high-visibility role where you'll shape the technical strategy for vertical-specific marketplace optimization, mentor talented engineers, and collaborate with world-class data scientists, product managers, and economists to push the boundaries of what's possible in mobility marketplaces.
What the Candidate Will Need / Bonus Points

• Lead technical strategy across 1+ year time horizons, setting the vision for vertical-specific marketplace optimization
• Design and build end-to-end ML solutions for demand forecasting, supply balancing, and matching optimization in large-scale distributed systems
• Develop sophisticated forecasting and matching approaches that combine machine learning with mathematical optimization and game theory
• Collaborate closely with cross-functional teams of engineers, data scientists, and product managers to deliver high-impact business solutions across three critical verticals:
• Airport Marketplace: Demand forecasting, supply/demand balancing, driver earnings prediction, and matching algorithms
• Reserve: Scheduled ride demand forecasting, supply balancing, driver price surge, and matching optimization
• Shared Rides: Shared ride marketplace optimization including Rider/Driver behavior, pricing, pooling algorithms and route optimization

Basic Qualifications

• Ph.D., M.S. or Bachelors degree in Computer Science, Machine Learning, Operations Research or a related technical field
• Minimum 6 years of experience leading deployment of ML models in large-scale production environments
• Proficiency in one or more programming languages such as Python, Scala, Java or Go
• Experience with distributed data systems such as Spark, Ray, and real-time processing frameworks
• Expertise in developing demand forecasting, matching algorithms, or pricing systems for multi-sided marketplaces
• Deep understanding of modern ML techniques, including deep neural networks, time series forecasting, and mathematical optimization

Preferred Qualifications

- Experience developing multi-year technical strategies and roadmaps for ML systems
- Ability to translate business problems into technical solutions with measurable impact
- Excellent communication and collaboration skills across engineering, product, and operations teams
- Expertise in reinforcement learning, causal machine learning, or multi-objective optimization
Experience with online experimentation (A/B testing) and causal inference methodologies

For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 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.