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Uber Machine Learning Engineer II - UberEats Feed 
United States, West Virginia 
959994535

12.03.2025

What the Candidate Will Do:

  • Innovate and productionize start-of-the-art recommendation models, and customize for Uber’s use cases.
  • Design and build the 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.

Basic Qualifications:

  • PhD in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences or 2 years minimum 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 innovative end-to-end Machine Learning systems.

Preferred Qualifications:

  • Proficiency in one or more coding languages such as Python, Java, Go, or C++.
  • Experience with any of the following: Spark, Hive, Kafka, Cassandra.
  • Publications at industry recognized ML conferences.
  • Experiences with integrating ML models into the backend system.
  • Experience in simplifying/converting business problems into ML problems.
  • Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
  • Strong communication skills and can work effectively with cross-functional partners.

For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year.