The Shopping Ranking Team at Uber is focused on enhancing shopping decisions for users through advanced machine learning and optimization techniques. This role involves designing and building machine learning models specifically for ranking and recommendation systems. Candidates will work collaboratively across various teams, contributing to both infrastructure and model development. The position offers the opportunity to engage in innovative projects that leverage large datasets to create impactful solutions.

• Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 4+ years of full-time engineering experience.
• 6+ years of experience in machine learning and building machine learning models.
• Experience working with multiple multi-functional teams including product, science, and product operations.
• Expertise in one or more object-oriented programming languages such as Python, Go, Java, or C++.
• Experience with big-data architecture, ETL frameworks, and platforms such as HDFS, Hive, MapReduce, or Spark.
• Working knowledge of the latest machine learning technologies and libraries such as PyTorch, TensorFlow, or Ray.
• Proven track record of being a fast learner and go-getter, with a willingness to step out of the comfort zone.

• Design and build machine learning models in the ranking and recommendation domain.
• Productionize and deploy these models for real-world application.
• Review code and designs of teammates, providing constructive feedback.
• Collaborate with product and cross-functional teams to brainstorm new solutions and iterate on the product.

• 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.