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Staff Machine Learning Engineer - Rider Intelligence

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Uber

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Location:
United States , Seattle

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Category:
IT - Software Development

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Contract Type:
Employment contract

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Salary:

232000.00 - 258000.00 USD / Year
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Job Description:

Rider Experience drives and enables the critical trip booking funnel within the Rides app that makes up almost all of the trip transactions and contributes tremendously to business growth. We actively explore algorithmic improvements to how we help millions of riders find and discover the right products every hour to move around the world, and power smart and intuitive experiences for them.

Job Responsibility:

  • Define and execute technical strategies, spanning from model and system architecture to business objectives and stakeholder alignment
  • Lead the design, development, and production of end-to-end ML solutions for large-scale distributed systems serving billions of trips
  • Lead and mentor a team of Machine Learning Engineers (MLEs), providing technical leadership, setting the vision, and guiding the team through the full development lifecycle—from ideation to model deployment and scaling

Requirements:

  • Ph.D., M.S. or Bachelor in Computer Science, Mathematics with focus on Machine Learning, or equivalent technical background with exceptional demonstrated impact
  • 8+ years experience leading the development and deployment of ML models in large-scale production environments at top-tier ML companies

Nice to have:

  • Expertise in search, recommendation systems, ranking/retrieval, or representation learning is highly desirable
  • Proven experience in ranking optimization across heterogeneous content types
  • Demonstrated success in leading cross-functional projects that deliver significant business impact
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 05, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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