Uber's AI Security team is focused on developing dynamic, data-driven security systems that enhance the company's Zero Trust Architecture. As an ML Engineer, you will work on innovative projects that integrate machine learning with security and infrastructure. Your role will involve translating business and security needs into machine learning tasks, building models, and deploying them in production. This position offers the opportunity to shape how Uber secures AI at scale.

• 3+ years of experience building and deploying ML models in production.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Strong foundation in ML algorithms including tree-based models and classical methods.
• Ability to analyze business and security requirements and translate them into ML use cases.

• 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.

• Employees at Uber are often offered comprehensive health, life, disability, and mental wellness benefits, along with wellbeing stipends, travel medical coverage, and monthly Uber credits for Rides and Eats. Employees also get generous paid parental leave, flexible time off, and family-planning support so they can care for themselves and their families at every stage.