Uber Senior ML Engineer - AI Security 

United States, West Virginia 

486404595

As a Senior ML Engineer, you’ll translate ambiguous business and security needs into concrete ML problems, design and iterate on solutions, and take them end-to-end into production. This is greenfield work at the intersection of ML, security, and infrastructure, shaping how Uber secures AI at scale.

1. 5+ years experience in formulating ML problems from ambiguous business requirements especially in risk, fraud, or security contexts
2. Proficiency across a broad range of ML algorithms: tree-based models (XGBoost, LightGBM), classical statistical models (logistic regression, SVMs), and deep learning architectures (CNNs, RNNs, Transformers), with the ability to select and apply the right approach based on context and data.
3. Hands-on experience with feature engineering, model development, and productionization of ML pipelines.
4. Proficiency in PyTorch, TensorFlow, or similar ML frameworks, and in Python or comparable languages for scalable, production-grade systems.

1. Proven ability to own ML systems end-to-end: from requirement discovery → feature design → modeling → deployment.
2. Deep experience with advanced ML techniques, including ensemble methods, neural networks, graph-based models, and handling challenges like imbalanced data, feedback loops, and iterative retraining.
3. Familiarity with large-scale data/infra systems (Kafka, Pinot, Hive, Cassandra, Spark, Flink).
4. Background in access control, authentication, or enterprise security systems.
5. Track record of technical leadership: mentoring engineers, driving cross-functional initiatives, or shaping ML/security strategy.

1. Translate business and security needs into well-defined ML problems.
2. Develop, iterate, and productionize ML models that drive risk-adaptive decisions in real-time.
3. Engineer features from Uber’s risk systems, logs, and contextual signals.
4. Integrate ML systems into Uber’s critical access pathways (containers, APIs, gateways, data).
5. Collaborate across Security, Risk, and Infra teams to deliver scalable, production-ready solutions.
6. Provide leadership by mentoring junior engineers, evangelize ML best practices, and help shape ML strategy within AI Security.

For San Francisco, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$198,000 per year - USD$220,000 per year.