Senior Staff Machine Learning Engineering Leader - Marketplace Simulation & Planning

This role sits within Uber's Mobility Marketplace team, focusing on pricing and incentives. The team optimizes pricing and incentives to balance the market, maximize revenue, and adapt dynamic trip pricing to marketplace conditions.

You'll work on some of Uber's most strategic marketplace challenges at a global scale, directly impacting the business.

Responsibilities include:

• Build and scale a high-performing team by attracting top talent and refining team structure. Mentor and coach ICs and managers for both technical and leadership growth.
• Lead ML modeling teams responsible for large-scale applied machine learning in forecasting and optimization.
• Shape long-term product and technical vision for the mobility marketplace.
• Collaborate cross-functionally with Data Science, Product, and Business to drive technical direction in systems and modeling frameworks.
• Define and influence product strategy and roadmap in partnership with Product and Business teams.
• Communicate vision effectively, representing engineering in leadership forums and strategic discussions.
• Translate strategy into execution with practical quarterly OKRs.
• Drive operational excellence by establishing metrics for product and engineering performance.

Requirements include:

• MS/PhD in Computer Science or equivalent experience.
• 10+ years of software development experience.
• 3+ years of experience as a people manager.
• Proven ability to work in and contribute to cross-functional teams.
• Experience leading teams managing production optimization systems (e.g., recommendation, search).
• Strong analytical skills.
• Hands-on experience with ML and optimization systems.

Preferred qualifications include:

• Strong organizational skills with experience in large, cross-functional teams.
• Excellent problem-solving, critical thinking, and communication skills.
• Deep understanding of CS fundamentals, software engineering principles, and development methodologies.
• Experience managing managers.
• Experience deploying ML technologies into products.
• Strategic thinker with a track record of driving technical and organizational innovation.

For New York, 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. More details can be found at the following link.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

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.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.