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Machine Learning Engineer II

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Uber

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Location:
United States , San Francisco

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Contract Type:
Employment contract

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Salary:

171000.00 - 190000.00 USD / Year

Job Description:

Uber's Marketplace is at the core of the business. The Earner Incentive team in Marketplace builds products and systems that empower drivers through targeted incentives, creating a more balanced and efficient marketplace while enhancing earnings and experience. The team owns the end-to-end incentive lifecycle, from ML-driven incentive generation to scalable online serving, answering questions such as who, where, when, how, and how much, powered by large-scale machine learning, optimization, and experimentation systems. These systems enable proactive, targeted incentives that shape supply, optimize earnings, and guide marketplace balance. We are seeking a Machine Learning Engineer to help build and scale the technical foundations behind Uber's driver incentive systems. You will be responsible for developing and productionizing large-scale ML models and decision systems that power both scheduled and near real-time incentive generation. In this role, you will collaborate with senior engineers, product managers, and data scientists to implement technical solutions, navigate trade-offs, and maintain reliable production systems. Your work will directly impact marketplace efficiency and empower earning opportunities for millions of drivers worldwide.

Job Responsibility:

  • Build, productionize, and maintain ML solutions and data pipelines for the large-scale systems that power Uber's driver incentives
  • Implement and iterate on advanced ML and optimization techniques to improve marketplace efficiency and reliability, directly impacting the earning opportunities of millions of drivers
  • Translate business requirements into actionable technical tasks and practical, production-ready code, navigating technical trade-offs to ensure system reliability
  • Develop a deep understanding of incentives, pricing, and marketplace dynamics to build systems that align with operational needs and business goals
  • Contribute to high engineering standards by participating in design and code reviews, maintaining robust testing, and ensuring the stability of production ML systems
  • Partner closely with engineers, product managers, and scientists to ensure the successful delivery of high-impact solutions to marketplace problems
  • Own technical workstreams from development through production rollout, ensuring consistent execution and measurable impact on your immediate team's goals

Requirements:

  • Bachelor's or M.S. degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related technical field, or equivalent practical experience
  • 2+ years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
  • Solid understanding of machine learning and statistical techniques, including deep learning (e.g., multi-task learning), tree-based models, and experimentation
  • Proficiency in at least one production-grade language (Python, Scala, Java, or Go) and familiarity with common ML frameworks (e.g., PyTorch, TensorFlow, or scikit-learn)
  • Solid software engineering fundamentals, including the ability to write clean, maintainable production code, conduct thorough code reviews, and implement testing best practices
  • Experience operating and monitoring ML models in a production setting, with a basic understanding of MLOps workflows
  • Strong learning mindset, proactive ownership, and effective communication skills
  • ability to collaborate effectively within cross-functional teams

Nice to have:

  • 3+ years of experience in software engineering specializing in applied ML methods
  • Ph.D. in Computer Science, Engineering, Mathematics, or a related field
  • Proven experience designing and crafting scalable, reliable, and reusable ML solutions using deep-learning techniques and statistical methods
  • Experience developing or deploying algorithms for pricing, matching, or incentive systems within a two-sided marketplace
  • Exposure to or experience with multi-armed bandits, reinforcement learning, or causal inference, specifically within production systems
  • Familiarity with large-scale data and ML infrastructure (e.g., Spark, Flink) and experience working with batch or real-time data processing pipelines
  • Ability to translate well-defined business problems into actionable ML tasks, prototype ideas quickly, and move projects from conception to production
  • Experience working on cross-functional or cross-org projects, partnering with Product, Scientists, and leads to shape technical strategies
  • A detail-oriented, truth-seeking mindset with a focus on producing and valuing analytical evidence to continuously improve technical solutions
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible to participate in a 401(k) plan
  • Various benefits

Additional Information:

Job Posted:
May 04, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
Job Link Share:

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