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Staff Machine Learning Engineer - Delivery Marketplace

Uber

$223,000 - $248,000
Aug 26, 2025
Seattle, WA, US
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Uber's Delivery Marketplace is looking to optimize real-time operations and improve efficiency and user experience by developing advanced machine learning solutions.

Requirements

  • Programming language (e.g. C, C++, Java, Python, or Go)
  • Large-scale training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
  • Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc
  • Experience in the development, training, productionization and monitoring of ML solutions at scale.
  • Experience in modern deep learning architectures and probabilistic models.
  • Experience in optimization (RL / Bayes / Bandits) and online learning.
  • Experience in causal inference/personalization/ranking

Responsibilities

  • Lead the design and development of machine learning solutions that optimize real-time operations across Uber's Delivery Marketplace.
  • Build advanced ML models using techniques such as reinforcement learning, deep learning, and optimization methods to improve efficiency and the user experience.
  • Lead and mentor a team of MLEs, providing technical leadership, setting the vision, and guiding the team through the end-to-end development process - from ideation to model deployment and scaling.
  • Collaborate closely with cross-functional teams (product managers, data scientists, engineers) to define high-impact problems and develop solutions that improve operational efficiency while delivering magical user experiences.
  • Solve complex, real-world problems using state-of-the-art forecasting, demand-supply models, and prediction models for food prep time, batching quality, and courier activity at restaurants.
  • Balance business objectives and user experience by developing objective functions that optimize both business performance and user satisfaction.

Other

  • Experience in a technical leadership role and mentoring junior engineers.