Manager - Machine Learning

Uber is looking for an Engineering Manager to support our Marketplace Investments Modeling team. As the eng lead, you will have ownership of all aspects of growing the team and relevant products. You will manage a high performing team that plays a crucial role in developing and optimizing budget and price level setting for Rides and EATS.

We are broadly part of the Marketplace (PIMS) org, a central pillar to Uber's core technology which includes pricing, incentives/investments, matching, surge, etc. for both mobility and delivery. Investments team builds ML models and data to make incentive spend allocation decisions at Uber. Every week we need to allocate incentive spend across multiple levers to trade-off between revenue, growth, and marketplace health. We are actively working on redesigning Pricing levers and expanding our footprint to Delivery as well.

For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 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. You will also be eligible for various benefits. More details can be found at the following link .

Uber is proud to be an Equal Opportunity/Affirmative Action 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 .

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.

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