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Sr Staff Machine Learning Engineer - Delivery Courier Pricing
Sr Staff Machine Learning Engineer - Delivery Courier PricingUber • San Francisco, CA, United States
Sr Staff Machine Learning Engineer - Delivery Courier Pricing

Sr Staff Machine Learning Engineer - Delivery Courier Pricing

Uber • San Francisco, CA, United States
5 days ago
Job type
  • Full-time
Job description

About the Role

The Courier Pricing team sits within Uber's Delivery Marketplace org and plays a key role in shaping pricing across food, grocery, and other delivery verticals. We work closely with cross-functional teams to develop scalable pricing products that keep our marketplace efficient, reliable, and ready to grow. As a Sr Staff Machine Learning Engineer, you'll build a world-class pricing system that efficiently prices every offer made to Uber's delivery partners-impacting hundreds of millions of consumers and millions of merchants worldwide.

What You Will Do

Technical Leadership & Innovation

  • Lead the design and implementation of advanced ML systems for courier pricing algorithms serving millions of couriers
  • Own end-to-end ML model lifecycle from research through production deployment and continuous optimization

Platform & Architecture

  • Build scalable ML architecture and feature management systems supporting Courier Pricing and broader Marketplace teams
  • Design experimentation frameworks enabling rapid testing of pricing algorithms using A / B, Switchback, Synthetic Control, and other experimental methodologies
  • Establish ML engineering best practices, monitoring, and operational excellence across the organization
  • Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms
  • Cross-Functional Impact

  • Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research
  • Work with Platform Engineering teams to ensure ML systems meet reliability and performance standardsInfluence technical roadmaps across multiple teams through technical leadership and strategic thinking
  • Team Development

  • Mentor and grow senior ML engineers, establishing technical standards and engineering culture
  • Lead technical discussions and architecture reviews for complex ML systems
  • Basic Qualifications

  • PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master's degree with 12+ years of industry experience
  • 10+ years of experience building and deploying ML models in large-scale production environments
  • Expert‑level proficiency in modern ML frameworks (TensorFlow, PyTorch) and distributed computing platforms (Spark)
  • Deep expertise across multiple areas including : Deep Learning, Causal Inference, Reinforcement Learning, Multi‑objective Optimization, and Algorithmic Game Theory
  • Proven track record of leading complex ML projects from research through production with significant measurable business impact
  • Strong programming skills in Python, Java, or Go with experience building production ML systems
  • Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
  • Technical leadership experience including mentoring senior engineers and driving cross‑team technical initiatives
  • Preferred Qualifications

  • Marketplace or two‑sided platform ML experience with understanding of supply‑demand dynamics and pricing mechanisms
  • Publications or patents in applied machine learning, particularly in areas relevant to optimization, pricing, or marketplace dynamics
  • Experience with causal inference methodologies and their application to business problems with network effects
  • Reinforcement learning experience in production environments with long‑term optimization and strategic agent considerations
  • Technical leadership experience including mentoring senior engineers and driving cross‑team technical initiatives
  • Experience with real‑time ML systems requiring low‑latency inference and high‑throughput model serving
  • Background in economics, operations research, or related quantitative disciplines with application to marketplace problems
  • For San Francisco, CA‑based roles : The base salary range for this role is USD$257,000 per year - USD$285,500 per year. For Sunnyvale, CA‑based roles : The base salary range for this role is USD$257,000 per year - USD$285,500 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 comp. You will also be eligible for various benefits. More details can be found at the following link https : / / www.uber.com / careers / benefits.

    Uber is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- https : / / docs.google.com / forms / d / e / 1FAIpQLSdb_Y9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA / viewform

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