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Uber Software Engineer II - Machine Learning 
United States, West Virginia 
200760249

06.09.2024

About the Role

- - - - 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.
  • Proficiency in one or more coding languages such as Python, Java, Go, or C++.
  • Experience with any of the following: Spark, Hive, Kafka, Cassandra.
  • Strong communication skills and can work effectively with cross-functional partners.

- - - - Preferred Qualifications ----

  • Publications at industry recognized ML conferences.
  • 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.

For New York, NY-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$158,000 per year - USD$175,500 per year.