Uber is looking for candidates with a passion for solving new and difficult problems with data to improve the Uber user experience and overall marketplace performance. The Driver Incentive team aims to design, evaluate, and build promotional products for drivers, addressing key business problems such as designing incentive structures, measuring causal impacts of promotions, and creating ML-driven optimizations for marketplace growth.
Requirements
- 4+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments, delivering measurable business impact over multiple quarters and making significant technical contributions
- Proficiency in programming languages such as Python, Scala, Java, or Go
- Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
- Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
- Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization)
- Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
- Experience in reinforcement learning and causal machine learning
Responsibilities
- Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems serving billions of trips
- Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
- Collaborate with the team leads to set the team's technical direction and own its implementation, providing technical mentorship to junior engineers
- Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems
Other
- Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
- Experience leading complex technical projects and influencing the scope and output of others
- Track record of translating ambiguous business problems into technical solutions and driving multi-functional projects
- Excellent communication skills to lead initiatives and collaborate effectively with cross-functional partners
