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.
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You will lead projects and drive cross-team collaboration with engineers across various product teams, including UberEats, Rides, FinTech, etc. As a result of your work, our team will deliver impact across various products and business lines. If you are interested in building product facing systems, working on complex system problems, improving user experience, and helping drive Uber's top-line metrics then Membership is the team for you.
What the Candidate Will Need
- Design and build Machine Learning models with optimization engines.
- Productionize and deploy these models for real-world application.
- Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.
- Write high-quality code and uphold standards for testing and coverage.
- Align the team on solutions to ambiguous problems and analyze the tradeoffs of different technical solutions
- Contribute to engineering cultivation in terms of quality, monitoring, and on-call practices.
- Find opportunities to improve how our team operates and promote standard processes
Basic Qualification
- Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 5+ years of full-time engineering experience.
- 3 + years of ML experience and building ML models
- Experience working with multiple multi-functional teams(product, science, product ops etc).
- Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
- Experience with big-data architecture, ETL frameworks and platforms.
- Solid understanding of latest ML technologies, and libraries.
- Proven track records of being a fast learner and go-getter, with willingness to get out of the comfort zone.
Preferred Qualifications
- Experience with the design and architecture of ML systems and workflows.
- Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
- Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
- Experience with optimizing Spark queries for better CPU and memory efficiency.
- Experience owning and delivering a technically challenging, multi-quarter project end to end
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 accommodations@uber.com.