**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. What the Candidate Will Do ---- - 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 Qualifications ---- - Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 6+ years of full-time engineering experience. - 4+ 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 For San Francisco, CA-based roles: The base salary range for this role is USD$218,000 per year - USD$242,000 per year. 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 [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits). 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 [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). 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.