Uber Corporate
Machine Learning Engineer
San Francisco, California, USA · Full-time
Sponsorship not specified$171k-$190kDetected 29 days ago
PythonAlgorithmsKafkaMachine LearningTensorFlowPyTorchSparkNLPCybersecurityZero TrustCommunicationCollaboration
About the role
- 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.
- 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.
- Engineer features from Uber's risk systems, logs, and contextual signals.
Responsibilities
- 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.
- Support framing business and security problems as ML tasks.
- Build and iterate ML models that enable risk-adaptive, real-time decisions.
- Deploy and maintain ML pipelines in production, ensuring reliability and scalability.
- Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress.
- 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.
- 3+ years experience building and deploying ML models in production, with hands-on work in feature engineering, training, and evaluation.
Requirements
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar).
- Collaborate with senior engineers to integrate ML into Uber's authentication and authorization systems. \\-\\-\\-\\- Basic Qualifications ---- 1.
Nice to have
- tree-based models (XGBoost, LightGBM), classical methods (logistic regression, SVMs), and exposure to neural networks (CNNs, RNNs, Transformers).
- 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.
Compensation
- The base salary range for this role is USD$171,000 per year - USD$190,000 per year.
Benefits
- What the Candidate Will Need / Bonus Points \\-\\-\\-\\- What the Candidate Will Do ---- 1.
- For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp.
Equal opportunity
- Uber is proud to be an Equal Opportunity employer.
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This listing is sourced directly from Uber Corporate's careers page and normalized into a canonical job model.