Machine Learning Engineer II - AI Security

Join to apply for the Machine Learning Engineer II - AI Security role at Uber

Join to apply for the Machine Learning Engineer II - AI Security role at Uber

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.

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.
Basic Qualifications

• 3+ years experience building and deploying ML models in production, with hands-on work in feature engineering, training, and evaluation.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar).
• Strong foundation in ML algorithms: tree-based models (XGBoost, LightGBM), classical methods (logistic regression, SVMs), and exposure to neural networks (CNNs, RNNs, Transformers).
• Ability to analyze business/security requirements and support translating them into ML use cases.
  

Preferred Qualifications

• Experience with risk, fraud, anomaly detection, or security-related ML systems.
• Familiarity with large-scale data/infra systems (Kafka, Hive, Spark, Flink, Pinot).
• Exposure to handling challenges such as imbalanced data, feedback loops, or iterative retraining.
• Strong communication skills and ability to work cross-functionally with infra, risk, and security teams.
  

What The Candidate Will Do

• 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.
  

For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Internet Marketplace Platforms

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