PhD Software Engineer Intern; Search), at Uber
Listed on 2026-06-06
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Software Development
Software Engineer, Machine Learning/ ML Engineer
2026 PhD Software Engineer Intern (Search), United States
We’re looking for PhD candidates to intern on the Search team during summer 2026 (12 weeks). You will be embedded in our engineering team and work closely with other specialists, software developers, and product managers. As a PhD intern, you will work on an exciting yet bold problem in depth and independently, under the supervision of an experienced engineer on that team.
About the Team
The Search Platform team is responsible for the Search experience on several product surfaces at Uber, enabling millions of users to find, discover, and explore rides, food, etc. Search has played an increasingly important role in bringing Uber closer to its vision.
What You’ll Do
- Drive exciting, ambitious, previously unsolved projects end to end
- Thrive in ambiguous product requirements
- Collaborate with product managers, data scientists and machine learning engineers closely
- 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 distributed systems, machine learning, or a related engineering field
- Candidates must have at least one semester/quarter of their education left following the internship
Preferred Qualifications
- Knowledge of underlying technical foundations of distributed systems, machine learning workflows, etc.
- Experience in one or more object-oriented languages, including C++, Java, Python, or Go.
- Ability to communicate effectively with both technical and business partners
- 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
- Experience with handling multimodal data in the industry
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