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Senior Staff Machine Learning Engineer - Trusted Identity

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Uber

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Location:
United States , Sunnyvale ▼

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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:

We are looking for an experienced Senior Staff Machine Learning Engineer to join the Account Integrity team within Trusted Identity engineering org at Uber. The Trusted Identity org plays a crucial role in our mission empower the users with secure and seamless digital experiences by establishing industry-leading standards for identity verification, and fraud prevention, while proactively safeguarding against the evolving landscape of AI-driven fraud.Our continued obsession for innovation in the space is essential to ensure safety as people interact on Uber's platform.

Job Responsibility:

  • Work with product, data science, and eng leadership to shape the technical roadmap and problem formulations for the team
  • Leverage algorithmic knowledge in machine. learning/optimization/statistics to design robust engineering solutions to positively impact Uber's business
  • Shape the MLE role and uplevel MLE talents in the org
  • Be responsible for the End to End of the product - ML model pipeline & system design, implementation, AB testing, and rollout. Work with the team to productionize the solutions at scale

Requirements:

  • 10+ years of industry experience developing machine learning models ( both classical and deep learning) and shipping ML solutions to production
  • Master’s degree in Computer Science, Engineering, Mathematics or related field
  • Strong problem-solving skills, with expertise in ML methodologies
  • Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems
  • Industry experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines
  • programming languages such as Python, Spark SQL, Presto, Go, Java

Nice to have:

  • PhD degree in Computer Science, Engineering, Mathematics or related field
  • Familiarity with multi-task learning, LLMs and anomaly detection
  • Fraud domain knowledge
What we offer:
  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible for various benefits

Additional Information:

Job Posted:
February 02, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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