Responsibilities
- Create and deploy production-level machine learning systems that enhance product functionality, supporting both cloud-based and on-site environments with limited resources.
- Construct and refine machine learning models tailored to industrial control system and operational technology security, including anomaly identification, threat detection, and natural language processing.
- Develop reliable data processing pipelines and ML workflows compatible with current data systems, handling both real-time and batch data needs.
- Work closely with security detection specialists to convert research prototypes into scalable, operational machine learning solutions.
- Coordinate with data engineering teams to define data specifications and implement monitoring systems for ML pipelines, ensuring traceability, version control, and consistent deployment.
- Support enhancements to machine learning infrastructure by building automated testing, continuous integration and deployment pipelines, and containerized deployment methods using Kubernetes and Docker.
- Assess and integrate cutting-edge machine learning research and open-source models into domain-specific security use cases.
- Diagnose and improve the performance of deployed ML models, focusing on reducing latency, improving accuracy, and optimizing resource consumption.
