Senior Staff Machine Learning Engineer - Core Services Engineering

We are looking for an experienced Senior Staff Machine Learning Engineer to join the Risk and Trust engineering organization at Uber. Our team plays a crucial role in empowering users with secure and seamless digital experiences by establishing industry-leading standards for identity verification, account integrity, and advanced fraud prevention. We proactively safeguard the platform against the evolving landscape of AI-driven fraud, ensuring safety and trust remain at the core of every interaction on Uber's platform. Our focus on fraud prevention is essential to protecting our users and maintaining the integrity of our global services.

About the Role

We are seeking a seasoned Senior Staff Machine Learning Engineer to join the Risk and Trust engineering organization at Uber, focusing on innovative fraud prevention and account integrity solutions. The Risk and Trust organization is central to Uber's mission of providing secure and seamless digital experiences. We focus on establishing industry-leading standards for identity verification, fraud prevention, and account integrity, while proactively defending against sophisticated, AI-driven threats. Our commitment to innovation in fraud prevention is essential to maintaining a safe and trusted environment for everyone who uses the Uber platform.

What You'll Do

• 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.

Basic Qualifications

• 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

Preferred Qualifications

• PhD degree in Computer Science, Engineering, Mathematics or related field
• Familiarity with multi-task learning, LLMs and anomaly detection
• Fraud domain knowledge

For San Francisco, CA-based roles: The base salary range for this role is USD $267,000 per year - USD $297,000 per year.