Senior Staff Machine Learning Engineer - Trusted Identity
About The Position
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.
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 Haves
- PhD degree in Computer Science, Engineering, Mathematics or related field
- Familiarity with multi-task learning, LLMs and anomaly detection
- Fraud domain knowledge
Responsibilities
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Industry
Transit and Ground Passenger Transportation
Number of Employees
5,001-10,000 employees
