Sr Staff Machine Learning Engineer- Consumer Incentives

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

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Various benefits

Job summary

Uber is seeking a Senior Staff Machine Learning Engineer to shape the ML strategy for Consumer Incentives in Sunnyvale. You will translate research advances into reliable products, lead cross‑team efforts, and drive measurable business impact at scale across hundreds of millions of users.

You will define the long‑term ML vision, own the roadmap, and mentor engineers while exploring reinforcement learning, foundation models, and generative AI to advance personalized incentives and optimization.

Qualifications

• 12+ years in ML with deep learning systems ownership.
• Proven ability to set technical strategy and influence roadmaps.
• Strong product intuition linking models to business outcomes.

Responsibilities

• Define long-term ML vision and roadmap for Consumer Incentives.
• Lead cross-team initiatives from problem framing to production deployment.
• Design models that improve incentive relevance and impact.
• Architect scalable ML systems including data pipelines and monitoring.
• Establish rigorous evaluation and causal measurement practices.
• Explore reinforcement learning, foundation models, and generative AI.
• Mentor engineers and raise technical decision-making quality.

Skills

ML leadership

Large-scale DL systems

Experimentation design

Optimization

Applied ML strategy

Education

Masters or PhD in CS/Engineering/Math

Job description

About The Role And Team

Operating across key business areas like grocery and food, the Consumer Incentives team drives Uber's growth and long-term profitability. We deliver products that create seamless, affordable, and enjoyable customer experiences by building AI/ML-powered intelligence and sophisticated distributed systems at scale for hundreds of millions of global users.

What You’ll Do

As a Senior Staff Machine Learning Engineer, you will shape the technical vision and long-term ML strategy for Consumer Incentives. You will tackle fundamental questions about how to personalize incentives, understand their incremental impact on consumer behavior, and optimize investment to deliver customer value and sustainable business growth.

This is a hands‑on technical leadership role spanning machine learning, optimization, experimentation, and large‑scale systems. You will lead initiatives across team boundaries, partner with engineering and cross‑functional leaders to define the roadmap, and translate advances in ML into reliable products with measurable business impact. Building on our established capabilities in deep learning and constrained optimization, you will also help identify and develop opportunities for reinforcement learning, foundation models, and generative AI.

• Set technical direction: Define the long‑term ML vision, architecture, and technical roadmap for Consumer Incentives, aligning investments with consumer needs and business priorities.
• Lead strategically important initiatives: Turn ambiguous problems into actionable technical strategies, and drive execution across teams from problem formulation and offline evaluation through experimentation, production deployment, and ongoing improvement.
• Advance personalization and optimization: Design models and algorithms that improve incentive relevance, estimate incremental impact, and optimize decisions under business and operational constraints.
• Architect scalable ML systems: Guide—and contribute directly to—the design and implementation of end‑to‑end ML systems, spanning data and feature pipelines, model training, inference, and monitoring, with a high bar for reliability, scalability, and maintainability.
• Connect scientific rigor to business outcomes: Establish strong approaches to model evaluation, experimental design, and causal measurement, balancing short‑term results with long‑term consumer value and sustainable growth.
• Translate emerging techniques into practical advances: Evaluate where reinforcement learning, foundation models, and generative AI can meaningfully improve our products, and lead promising approaches from exploration to production.
• Build alignment across functions: Partner with product management, data science, operations, and engineering leaders to prioritize opportunities, make technical trade‑offs, and deliver shared outcomes.
• Multiply the impact of others: Mentor engineers and technical leaders, raise the quality of technical decision‑making, and build reusable capabilities that accelerate work across teams.

Basic Qualifications

• Masters degree or Ph.D in Computer Science, Engineering, Mathematics
• 12+ years of ML experience, including significant work on large‑scale deep learning systems.
• Demonstrated ownership of high‑impact ML systems such as search, recommendations, personalization, targeting.
• Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level.
• Strong product intuition and ability to connect model improvements to business outcomes.

Preferred Qualifications

• Track record of successfully launching multi‑year, multi‑org ML initiatives that drove step‑change business outcomes.
• Successfully championed and driven the adoption of multi‑year technical roadmaps across multiple large engineering organizations.
• Elevated engineering standards through mentorship and technical leadership, establishing org‑wide best practices.

For New York City, NY-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For Seattle, WA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.

For all US locations, 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.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full‑time in-office presence.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.