Machine Learning Engineer II – Security

About The Role Uber’s newly formed AI Security team, part of the Core Security Engineering organization, is building the foundation for dynamic, data-driven security systems. We’re evolving Uber’s Zero Trust Architecture (ZTA) to be more risk-adaptive across authentication and authorization, moving beyond static rules and manual approvals toward real-time, ML-driven access decisions that secure both humans and AI agents.

As an ML Engineer, you’ll help translate business and security needs into concrete ML problems, build models and features, and take them into production. You’ll be part of a team working on greenfield projects at the intersection of ML, security, and infrastructure, shaping how Uber secures AI at scale.

Responsibilities

• Support framing business and security problems as ML tasks.
• Build and iterate ML models that enable risk-adaptive, real-time decisions.
• Engineer features from Uber’s risk systems, logs, and contextual signals.
• Deploy and maintain ML pipelines in production, ensuring reliability and scalability.
• Collaborate with senior engineers to integrate ML into Uber’s authentication and authorization systems.

Qualifications

We offer a competitive salary range and benefits package. For more information, please visit our website.

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