The Machine Learning Engineer role at UberEats focuses on enhancing the Feed, which is crucial for both users and merchants. This position involves tackling challenging problems related to recommendation systems and machine learning. The engineer will work on developing and productionizing innovative models tailored for Uber's use cases. Collaboration with cross-functional teams is essential to improve the overall quality and performance of the Feed Model.

• PhD in relevant fields or a minimum of 2 years of industry experience with a strong focus 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 building and productionizing end-to-end Machine Learning systems.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.
• Experience with technologies such as Spark, Hive, Kafka, or Cassandra.
• Strong communication skills and the ability to work effectively with cross-functional partners.

• Innovate and productionize state-of-the-art recommendation models for Uber's use cases.
• Design and build end-to-end large-scale ML systems to enhance the HomeFeed Recommendation.
• Improve the Feed Model ML Quality, Model Serving foundation, and 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.