Senior ML Engineer - Strategy, Scalable Systems & Impact

Uber; San Francisco (CA); On-site; USD 267,000 - 297,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k)

Various benefits

Job summary

Uber’s Consumer Incentives team is focused on improving growth and long-term profitability. This Senior Staff Machine Learning role is based in San Francisco, CA (onsite) and involves shaping long-term ML strategy while leading hands-on work across personalization, optimization, experimentation, and scalable ML systems.

The role requires a Master’s or Ph.D. in CS/Engineering/Math and 12+ years of ML experience with large-scale deep learning, plus ownership of high-impact ML systems such as

Qualifications

• Master’s degree or Ph.D. in Computer Science, Engineering, or Mathematics.
• 12+ years of ML experience with large-scale deep learning systems.
• Ownership of high-impact ML systems such as search, recommendations, personalization, or targeting.

Responsibilities

• Define the long-term ML vision, architecture, and technical roadmap for Consumer Incentives.
• Drive execution from problem formulation and offline evaluation through experimentation, production deployment, and improvement.
• Design models to improve incentive relevance, estimate incremental impact, and optimize decisions.
• Lead end-to-end ML systems across data pipelines, training, inference, and monitoring for reliability and scalability.
• Build evaluation and measurement approaches, including model evaluation and causal measurement.

Skills

ML experience

Deep learning

Technical leadership

Product roadmaps

Strategic thinking

Education

Master’s or Ph.D. in CS/Engineering/Math

Job description

Uber’s Consumer Incentives team is focused on improving growth and long-term profitability. This Senior Staff Machine Learning role is based in San Francisco, CA (onsite) and involves shaping long-term ML strategy while leading hands-on work across personalization, optimization, experimentation, and scalable ML systems.

The role requires a Master’s or Ph.D. in CS/Engineering/Math and 12+ years of ML experience with large-scale deep learning, plus ownership of high-impact ML systems such as