The Consumer Incentives team at Uber focuses on enhancing customer experience and driving business growth across various verticals, including food and grocery. This role involves providing technical leadership in machine learning to optimize incentive efficiency and user experience. The position requires collaboration with cross-functional teams and managing end-to-end project execution. The ideal candidate will have extensive experience in ML engineering and a strong background in deep learning and optimization algorithms.

• Master's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field with 6+ years of full-time ML engineering experience.
• Expertise in deep learning and optimization algorithms.
• Experience with ML frameworks such as PyTorch and TensorFlow.
• Experience building and productionizing innovative end-to-end Machine Learning systems.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.
• Strong communication skills and the ability to work effectively with cross-functional partners.

• Identify strategic technical investments to push the efficiency frontier and boost business growth.
• Lead teams to design and implement ML/optimization solutions to meet ambitious business goals.
• Manage end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation.
• Collaborate with cross-functional teams, including product, operations, and science partners.

• Employees at Uber are often offered comprehensive health, life, disability, and mental wellness benefits, along with wellbeing stipends, travel medical coverage, and monthly Uber credits for Rides and Eats. Employees also get generous paid parental leave, flexible time off, and family-planning support so they can care for themselves and their families at every stage.