Uber Software Engineer II - Machine Learning 

United States, West Virginia 

70993750

About the Role

The Membership team is responsible for developing and reinventing the Uber and UberEats app to be a member-first experience from: price to perks . You will be on a super collaborative team designed to maximize your ability to deliver results. You will be working on code that's closest to the eaters today and consumers in the future. Your work will impact the foundations of Uber around the world. You will be building the biggest lever for Uber.

For an industry synonymous with convenience, it’s ironic that the first thing you have to do when you pick up your phone is make a bunch of repetitive decisions. Uber Members will get something nobody else does: a single platform across all their on-demand needs, anywhere in the world, that always guarantees the best: price, selection, priority, and perks. To enable these initiatives, we invest heavily in ML and optimization tech stacks, including data ETL, feature store, dev & viz tooling, model training, serving, storage and backtest solutions.

We are actively seeking individuals who excel in problem-solving and critical thinking, are proficient in coding, with proven track records of learning and growth, and have a deep interest in ML model, feature and infrastructure development. Candidates will have the opportunity to work across various lines, from infrastructure development to ML model creation, offering a diverse and enriching experience.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

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.

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .