Staff Machine Learning Engineer Job at Uber (San Francisco)

Staff Machine Learning Engineer

Uber

Location:
United States , San Francisco ▼
Sunnyvale

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

232000.00 - 258000.00 USD / Year

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Job Description:

The Marketplace Signals team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals—such as eyeball ETA, spinner time, and supply reliability indicators—are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions.

Job Responsibility:

Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts)
Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized
Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases
Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals
Ensure consistency and reliability across Uber's platform by maintaining high-quality marketplace signals that inform rider and driver experiences
Reduce technical debt by streamlining signal infrastructure and minimizing redundant computations
Work with real-time streaming data and large-scale distributed systems to ensure Uber's signals are up-to-date and responsive to market dynamics.

Requirements:

Ph.D. or M.S. in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields
6+ years of industry experience in machine learning, including building and deploying ML models at scale
Experience in modern deep learning architectures and probabilistic modeling
Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
Solid understanding of MLOps practices, including design documentation, testing, and source code management with Git
Advanced skills in the development and deployment of large-scale ML models and optimization algorithms
Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.

Nice to have:

Expertise in developing causal inference methodologies, experimental designs, and advanced analytical methods
Strong experience in building a wide range of models (e.g. causal inference, optimization, ML) for business applications
Experience in algorithm development and rapid prototyping
Design, develop, and operationalize econometric models to assess challenging causal problems such as product incrementality and long-term value
Propose, design, and analyze large scale online experiments and interpret the results to draw actionable conclusions
Ability to drive clarity on the best modeling solution for a business objective
Collaborate with cross-functional teams across disciplines such as product, engineering, and operations to drive system development end-to-end from generating ideas to productionizing.

What we offer:

Bonus program
Equity award
401(k) plan
Various benefits

Additional Information:

Job Posted:
May 14, 2026

Employment Type:

Fulltime

Work Type:

On-site work

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