(US) Principal ML System Engineer

- Define experiment tracking standards - Define feature store architecture - Define model registry standards - Define reference architectures and standards for scalable ML pipelines - Define security architecture for ML platform - Define technical vision and strategy for ML platform - Design secure cost efficient integration patterns with APIs and data sources - Drive CI CD for models and ML pipelines - Ensure authentication and role based access control adoption - Establish reliability observability and performance practices for ML systems - Implement audit logging and compliance monitoring - Implement monitoring, alerting, and automated remediation - Lead mentorship and technical guidance for engineering teams - Set MLOps best practices for models and workflows - Translate business objectives into technical roadmap