Uber - Sunnyvale, CA

posted about 2 months ago

Full-time - Mid Level
Remote - Sunnyvale, CA
Transit and Ground Passenger Transportation

About the position

The Sr Machine Learning Engineer position at Uber involves working on multiple teams focused on enhancing the company's marketplace through advanced machine learning and optimization techniques. The role is pivotal in the Coordinated Structural Pricing team, which is dedicated to setting rider and driver prices to maintain marketplace balance. This team is engaged in developing offline models that simulate and optimize pricing levels to foster growth in trips and gross bookings while ensuring marketplace reliability and venture capital neutrality. A significant project currently underway is the development of a new pricing and simulation technology called Pricer-Planner, which explores various simulation methodologies, including both machine learning-driven and structural economics-driven approaches. Additionally, the Marketplace Intelligence team plays a crucial role in Uber's core business by aiming to improve customer experience and reduce churn through intelligent solutions. This team is tasked with leveraging machine learning, data science, and economic principles to create scalable platforms that enhance Uber's impact on the transportation industry. The Sr Machine Learning Engineer will be responsible for driving high-impact projects that optimize consumer marketplace experiences using advanced optimization techniques, machine learning, and causal inference. In this role, the candidate will design and build machine learning models integrated with optimization engines, ensuring these models are production-ready for real-world applications. The engineer will also review code and designs from teammates, providing constructive feedback to enhance team performance. Collaboration with product and cross-functional teams will be essential to brainstorm innovative solutions and iterate on product development.

Responsibilities

  • Design and build Machine Learning models with optimization engines.
  • 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 related field, with 4+ years of full-time engineering experience or PhD with 2+ years of full-time engineering experience.
  • 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++).

Nice-to-haves

  • 3+ years of ML/economics experience and building ML/economic models.
  • Experience with the design and architecture of ML systems and workflows.
  • Experience with building algorithmic solutions 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 optimizing Spark queries for better CPU and memory efficiency.
  • Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, JAX, Ray, etc.
  • Experience owning and delivering a technically challenging, multi-quarter project end to end.
  • Experience with big-data architecture, ETL frameworks and platforms, such as HDFS, Hive, MapReduce, Spark, etc.

Benefits

  • Participation in Uber's bonus program.
  • Eligibility for equity awards and other types of compensation.
  • Various health and wellness benefits as detailed on Uber's careers page.
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