## **About the Team** ## Rider Experience drives and enables the critical trip booking funnel within the Rides app that makes up almost all of the trip transactions and contributes tremendously to business growth. Our team actively explores personalization algorithmic and UX improvements in product recommendations and merchandising to help millions of riders find and discover the right products every hour to move around the world, and power smart and intuitive experiences for them. The work of the team has a large biz impact for Rides, while helping with mobility reliability and marketplace balance, and maintaining a high bar for rider experience. ## **About the Role** Staff ML engineers at Uber are passionate yet pragmatic technologists who are able to translate business insight and goals into well-formulated ML projects and scalable solutions to deliver impact. They are not only collaborative role models but also approachable leaders, humble teachers while also effective in helping the team in project execution. You will work with talented people in product, science, operations, and platform teams to help build and optimize our Rider Experience products. The role requires technical chops as well as strong communication & leadership skills. ## **What You Will Do** - Defining and driving ML solutions for key strategic problems in the space of product recommendations and merchandising: help riders find and complete rides with the right products, understanding their ride context and modeling their intent while attending to Uber’s business goals, marketplace conditions and efficiencies. - Provide technical leadership to a passionate, experienced, and diverse engineering team. Manage project priorities, deadlines and deliverables and design, develop, test, deploy and maintain ML solutions.  Classification, regression, and multi-task learning are in our toolbox. - Raise the bar of ML engineering by improving best practices, producing exemplary code, documentation, automated tests and thorough & precise monitoring, and applying model debugging & interpretation techniques. - Partner with product owners, data scientists and business teams to translate key insights and business opportunities into technical solutions ## **Basic Qualifications** - Bachelor’s degree in Computer Science, Engineering, Mathematics or related field - 4+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation - Strong problem-solving skills, with expertise in ML methodologies - Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems) - Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines; programming languages such as Python, Spark SQL, Presto, Go, Java ## **Preferred Qualifications** - 6+ years of experience in software engineering specializing in applied ML methods - Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods. - Innate truth-seeker who values and produces analytic evidence and insight, as well as translating them and business goals into technical problems and solutions. - 2+ years of experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team’s strategies - Passionate about helping junior members grow by inspiring and mentoring engineers - Resilience, determination, ownership mindset 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 [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.