Job Information
Uber Staff Machine Learning Engineer - Driver Incentives in San Francisco, California
About the Role
We are looking for candidates with a passion for solving new and difficult problems with data. In this role, you will be able to use your strong quantitative skills in the fields of machine learning, statistics, and/or operations research to improve the Uber user experience as well as the overall marketplace performance. You'll be joining the Driver Incentive team to design, evaluate, and build promotional products for drivers
As a Staff machine learning engineer you will solve key business problems including designing incentives structures for drivers, measuring causal impacts of promotions, and creating ML-driven optimizations for marketplace growth. You will work hand in hand with product, engineering, and operations on new product launches, experiment design and algorithm development. We are a fast-moving team and are looking for creative and curious minds to join us!
What You Will Do
Build statistical, optimization, and machine learning models for applications including pricing, targeting, and experimentation.
Work with engineers and product managers to turn data science prototypes into robust, reliable machine learning (ML) solutions.
Use data to understand product performance and to identify improvement opportunities.
Solve ambiguous, challenging business problems using data-driven approaches.
Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
Develop new methodologies for data science including modeling, coding, analytics, optimization, and experimentation.
Collaborate with cross-functional teams such as product, operations, and marketing to drive system development end-to-end from conceptualization to final product.
Basic Qualifications
Ph.D. or M.S. in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
6+ years of industry experience in machine learning, including building and deploying ML models at scale.
Experience in modern deep learning architectures and probabilistic modeling
Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn),
Solid understanding of MLOps practices, including design documentation, testing, and source code management with Git.
Advanced skills in the development and deployment of large-scale ML models and optimization algorithms
Strong business and product sense: ability to shape vague questions into well-defined analyses and success metrics that drive business decisions.
Preferred Qualifications
Expertise in developing causal inference methodologies, experimental designs, and advanced analytical methods.
Strong experience in building a wide range of models (e.g. causal inference, optimization, ML) for business applications.
Experience in algorithm development and rapid prototyping.
Design, develop, and operationalize econometric models to assess challenging causal problems such as product incrementality and long-term value
Propose, design, and analyze large scale online experiments and interpret the results to draw actionable conclusions.
Ability to drive clarity on the best modeling solution for a business objective
Collaborate with cross-functional teams across disciplines such as product, engineering, and operations to drive system development end-to-end from generating ideas to productionizing.
For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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.
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://docs.google.com/forms/d/e/1FAIpQLSdb_Y9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA/viewform