Machine Learning Engineer: Building Intelligent Shopping Systems

4 weeks ago

Sunnyvale, California, United States Uber Full time
About the Role

At Uber, we're on a mission to revolutionize the way people shop. Our Shopping Ranking Team is at the forefront of this effort, leveraging cutting-edge Machine Learning (ML) and Optimization techniques to build scalable and reliable shopping intelligence ranking and recommendation systems.

We're seeking talented individuals who excel in problem-solving and critical thinking, with a proven track record of learning and growth. As a Machine Learning Engineer on our team, you'll have the opportunity to work across various lines, from infrastructure development to ML model development, productionalization, and more.

Key Responsibilities
  • 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.
Requirements
  • Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics, or a related field, with 2+ years of full-time engineering experience.
  • 1+ years of ML experience and building ML models.
  • Experience working with multiple multi-functional teams (product, science, product ops, etc.).
  • Expertise in one or more object-oriented programming languages (e.g., Python, Go, Java, C++).
  • Experience with big-data architecture, ETL frameworks, and platforms, such as HDFS, Hive, MapReduce, Spark, etc.
  • Working knowledge of latest ML technologies and libraries, such as PyTorch, TensorFlow, Ray, etc.
  • Proven track records of being a fast learner and go-getter, with a willingness to get out of the comfort zone.
Preferred Qualifications
  • Experience with building ranking and recommendation systems in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
  • Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure, and optimization constraints, and delivering business impact.
  • Experience with design and architecture of ML systems and workflows.
  • Experience owning and delivering a technically challenging, multi-quarter project end to end.
Compensation and Benefits

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

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of compensation. You will also be eligible for various benefits. More details can be found at the following link: Uber Benefits.

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