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2025 PhD Software Engineer Intern – Shared Rides
| Company | Uber |
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| Location | Seattle, WA, USA |
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| Salary | $67 – $67 |
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| Type | Internship |
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| Degrees | PhD |
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| Experience Level | Internship |
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Requirements
- 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
Responsibilities
- 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
- Have a passion to make Uber better for our customers
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
