Staff ML Engineer: Real-Time Marketplace Optimizer

Uber; Sunnyvale (CA); On-site; USD 232,000 - 258,000; Full time

Benefits offered by this job

Bonus program

Equity

401(k)

Benefits

Job summary

Uber's Marketplace Matching team builds real-time decision systems to match riders and drivers across a global two-sided marketplace. The Staff ML Engineer will own major optimization charters, set technical direction, and lead ambiguous 0→1 problems from formulation through large-scale production deployment.

The role blends machine learning, sequential decision-making, optimization, and marketplace dynamics, with collaboration across engineering, applied science, economics, product, and

Qualifications

• 8+ years of ML industry experience or 6+ with a PhD.
• Experience building large-scale production ML systems with online inference.
• Deep expertise in ML including deep learning and RL; decision-making under uncertainty.
• Ability to frame ambiguous problems as tractable ML or decision problems and ship to production.
• Strong BE programming and systems skills; able to design production-quality ML and optimization systems.

Responsibilities

• Set technical direction and own major charters for real-time matching optimization and ML systems.
• Design matching objectives and policies balancing rider, driver, and platform goals.
• Develop and productionize ML-based decision systems for sequential and multi-agent environments.
• Apply RL, probabilistic modeling, deep learning, causal inference to large-scale marketplace problems.
• Explore MPC and feedback-control approaches to adapt matching as conditions evolve.
• Build behavioral models of rider/driver responses and incorporate into optimization.
• Develop simulation, experimentation, and causal measurement for policy evaluation.
• Lead ambiguous 0→1 technical efforts from formulation to production inference and integration.
• Identify new algorithms or modeling approaches to materially improve marketplace performance.
• Collaborate with engineering, economics, product, and operations; mentor senior engineers.

Skills

Machine learning

Reinforcement learning

Optimization

Sequential decision making

Production ML systems

Cross-functional leadership

Education

Bachelor's degree in CS/ML/Engineering/Math/Stats

PhD in ML/RL/Control/Optimization/Robotics/OR/Statistics

Job description

Uber's Marketplace Matching team builds real-time decision systems to match riders and drivers across a global two-sided marketplace. The Staff ML Engineer will own major optimization charters, set technical direction, and lead ambiguous 0→1 problems from formulation through large-scale production deployment.

The role blends machine learning, sequential decision-making, optimization, and marketplace dynamics, with collaboration across engineering, applied science, economics, product, and