Sr Staff Machine Learning Engineer- Consumer Incentives

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 Uber’s growth and long-term profitability across major business areas like grocery and food. In this Senior Staff Machine Learning role, you will help shape the long-term ML strategy while leading hands-on technical work across personalization, optimization, experimentation, and scalable ML systems.

This position is based in San Francisco, CA (onsite) and supports measurable business outcomes for hundreds of millions of global users by building AI/ML-powered intelligence and distributed systems at scale.

What you’ll do

• Define the long-term ML vision, architecture, and technical roadmap for Consumer Incentives, aligning investments with consumer needs and business priorities.
• Convert ambiguous problems into actionable technical strategies, driving execution from problem formulation and offline evaluation through experimentation, production deployment, and ongoing improvement.
• Design models and algorithms to improve incentive relevance, estimate incremental impact, and optimize decisions under business and operational constraints.
• Lead and contribute to end-to-end ML systems across data and feature pipelines, training, inference, and monitoring, with emphasis on reliability, scalability, and maintainability.
• Build evaluation and measurement approaches, including model evaluation, experimental design, and causal measurement, balancing short-term results with long-term consumer value.
• Assess opportunities for reinforcement learning, foundation models, and generative AI, and move promising work from exploration to production.
• Partner with product management, data science, operations, and engineering leaders to prioritize work, manage technical tradeoffs, and deliver shared outcomes.
• Mentor engineers and technical leaders, improving the quality of technical decisions and creating reusable capabilities across teams.

Requirements

• Master’s degree or Ph.D. in Computer Science, Engineering, or Mathematics
• 12+ years of ML experience, including substantial work on large-scale deep learning systems
• Proven ownership of high-impact ML systems such as search, recommendations, personalization, or targeting
• Ability to set technical strategy for a large organization and influence product roadmaps at the executive level
• Strong product intuition with a clear connection between model improvements and business outcomes

Preferred qualifications

• Track record of launching multi-year, multi-org ML initiatives that delivered step-change business results
• Experience championing and driving adoption of multi-year technical roadmaps across large engineering organizations
• Raised engineering standards through mentorship and technical leadership, establishing org-wide best practices

Compensation and benefits

Salary range: USD 267,000 - 297,000 per year.

• Eligible to participate in Uber’s bonus program
• May be offered an equity award and other types of compensation
• Eligible to participate in a 401(k) plan
• Eligible for various benefits

Additional role details

• Unless approved for full remote work, employees must spend at least 50% of their time in-office
• Some roles may require full-time in-office presence; ask your Recruiter for specifics for this role
• Base salary ranges for this role are the same across multiple listed U.S. locations, including San Francisco