The Machine Learning Engineer role at UberEats focuses on enhancing the Feed, which is crucial for both users and merchants. This position involves innovating and productionizing advanced recommendation models tailored for Uber's unique use cases. The engineer will work on large-scale ML systems that power the HomeFeed Recommendation and improve the overall ML quality and data foundation. Collaboration with cross-functional teams is essential to drive impactful solutions.

• PhD in relevant fields such as Computer Science, Electrical Engineering, Mathematics, or Statistics with recommendation system research experience or a minimum of 3 years of industry experience focused on machine learning and recommendation systems.
• Expertise in deep learning, recommendation systems, or optimization algorithms.
• Experience with ML frameworks such as PyTorch and TensorFlow.
• Experience in building and productionizing innovative end-to-end Machine Learning systems.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.

• Innovate and productionize state-of-the-art recommendation models customized for Uber's use cases.
• Design and build end-to-end large-scale ML systems to power the HomeFeed Recommendation.
• Improve the Feed Model ML Quality, Model Serving foundation, and the Data foundation.
• Collaborate with cross-functional and cross-team stakeholders.

• 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.