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Sr Staff Machine Learning Engineer - Ads

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Uber

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Location:
United States , San Francisco ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

267000.00 - 297000.00 USD / Year
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Job Description:

Ads is a growing business at Uber. As part of this team, you will get an opportunity to influence the evolution of ads platform while delivering a lot of impact.

Job Responsibility:

  • Provide technical leadership, and drive technical direction for the ads delivery area
  • Work with cross-functional teams to find opportunities and implement enhancements to improve consumer experience and unlock value for advertisers and Uber

Requirements:

  • Technical leadership and drive technical direction for ads delivery area
  • Lead the design and implementation of advanced ML systems for all ads products at Uber
  • Own end-to-end ML model lifecycle from research through production deployment and continuous optimization
  • Build scalable ML architecture and feature management systems supporting ads marketplace
  • Establish ML engineering best practices, monitoring, and operational excellence across the organization
  • Create platform abstractions that enable other ML engineers to iterate faster on improvements
  • Collaborate with ads marketplace product and science teams to productionize cutting-edge ML research
  • Work with platform engineering teams to ensure ML systems meet reliability and performance standards
  • Influence technical roadmaps across multiple teams through technical leadership and strategic thinking
  • Mentor and grow senior ML engineers, establishing technical standards and engineering culture
  • Lead technical discussions and architecture reviews for complex ML systems
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • All full-time employees are eligible to participate in a 401(k) plan
  • Eligible for various benefits

Additional Information:

Job Posted:
March 19, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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