What the Candidate Will Do -

• 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 problem

- Basic Qualifications -

• Ph.D., M.S. or Bachelor’s degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
• 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

- Preferred Qualifications -

• Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
• 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 partnersExperience in reinforcement learning and causal machine learnin

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
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 the Candidate Will Do -

• 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

• Basic Qualifications -

• Ph.D., M.S. or Bachelor’s degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact

• 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)

• Preferred Qualifications -

• Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior

• 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 partnersExperience in reinforcement learning and causal machine learning

• For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 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