2025 PhD Software Engineer Intern (Shared Rides), United States

We’re looking for PhD candidates in the machine learning and optimization domain to intern on our Shared Rides team during summer 2025 (12 weeks). You will be embedded in an engineering team and work closely with other specialists, data scientists, and product managers. As a PhD intern, you will work on an exciting yet bold problem in depth independently, under the supervision of an experienced engineer on that team. ## **About the Role** At Uber, we work on many ambitious engineering products covering many lines of business as well as the underlying platform technologies that power those businesses. We foster growth and increase profitability of Uber by pushing the frontiers of machine learning, constrained optimization, statistics, data science and economics and developing highly reliable and scalable platforms to accelerate Uber’s impact on the transportation industry. As a PhD software engineer intern, you will have a lot of opportunities to work with product managers, data scientists and, of course, engineers from different teams. You will have an opportunity to learn how to iterate over a product for greater success while demonstrating your area of expertise (machine learning, statistics, constrained optimization, distributed system, etc.). This is a unique opportunity to grow your skills with real-world experience and do highly impactful, yet fun work at the same time. It is an ambitious yet rewarding job! **About the Team** The **Shared Rides** team mission is to provide a rideshare service at a substantially lower price point to a taxi or UberX via sharing the cost of the driver amongst multiple riders. We are developing a product which can achieve this lower cost while providing Riders with a predictable and defect-free experience and also generating sustainable earnings for Drivers and unlock the next frontier of growth for Uber. This team delivers all aspects of shared rides, from the experiences shown to riders and drivers, the routing and matching algorithms to make efficient sharing, and pricing to predict where we will be able to generate the greatest cost savings and convert the most riders. We work to identify the right trade offs between timeliness and costs, and build experiences to surface these trade offs. Walking, waiting, scheduling and routing all provide opportunities for us to drive efficiencies to continuously push prices lower for our customers. We push this to extremes with our shuttle products allowing for highly efficient trips This is a great opportunity to build out new tech for this growing business. The team addresses novel, large-scale vehicle routing problems in real-time. At any given time, we have tens of thousands of sharing requests and drivers looking for work in a city. Our jobs are to develop algorithms and models that identify who is the best driver to complete a given request, what is the lowest price that can be offered to the rider at a given point of time given the expected density of demand, how to batch trips together that have similar routes, and when is the best time to make the dispatch. As you can imagine, such complex, open-ended modeling and optimization problems come with many fascinating challenges related to time and space complexity, novel and domain-specific search heuristics, and technical, operational, and business constraints. ## **What You'll Do** - Drive exciting, ambitious, previously unsolved projects from end to end - Thrive in ambiguous product requirements - Collaborate with product managers and data scientists closely - Develop optimization algorithms to generate high coverage, direct and meaningful route networks for riders - Create machine learning models to predict marketplace metrics and conditions, and rider behavior to optimize pricing and maximize efficiency - Make data driven decisions, with exceptional execution - Be motivated to own projects and push them forward with independence - Most importantly, have a passion to make Uber better for our customers ## **Basic Qualifications** - Currently enrolled in a Ph.D. program studying machine learning, data mining, artificial intelligence, constrained optimization, statistics, or a related quantitative field - Candidates must have at least one semester/quarter of their education left following the internship - Knowledge of underlying technical foundations of statistics, machine learning, optimization, or systems etc. - Experience in one or more object-oriented languages, including C++, Java, Python, or Go - Experience with SQL and related database concepts ## **Preferred Qualifications** - Expertise related to pricing optimization and related applications in machine learning - Expertise and experience in numerical optimization, including linear/mixed integer and heuristic methods - Experience with statistical and machine learning methods for large, complex graph-structured and/or geospatial datasets - Excellent written, verbal, and visual communication for technical and non-technical audiences - Experience in simplifying/converting business problems into technical problems - Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation - Experience presenting at industry recognized academic conferences and a good publishing record For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. You will also be eligible for various 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.