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About the role
- Cyber Machine Learning Engineer building production-ready models to detect threats and anomalies for a leading security firm. Collaborating on innovative solutions to enhance cyber defense capabilities.
Responsibilities
- Build, train, and package production-ready models to detect advanced persistent threats and anomalous or suspicious activity
- Implement model performance observability to monitor and mitigate data drift, false positives, and resource utilization
- Identify new opportunities for effective applications of machine learning to unique cyber defense use cases
- Keep aware of latest research in machine learning and cybersecurity
- Demonstrate a history of intellectual curiosity
- Work on the cutting-edge of production systems for cybersecurity
- Contribute to novel and impactful work, using machine learning and cybersecurity expertise to enable and automate real-time detection and defense against threat actors
- Incorporate open-source tools, innovative methods, and cloud resources to cut down on false positive alerts and time to detection
- Implement continuous integration and delivery to limit manual testing and troubleshooting
- Build your experience in cyber defense and machine learning, while developing models and software that will defend the nation
Requirements
- 2+ years of experience with cyber threat hunting and analysis of compromises within security telemetry such as endpoint and network data
- 2+ years of experience training and monitoring machine learning models for use with batch data and streaming data
- Experience using Python
- Experience with MLOps practices, including CI / CD
- Experience packaging and deploying production-level models using Docker or Kubernetes
- Experience with SIEM technologies such as Splunk or Elastic Stack
- Experience with MITRE ATT & CK framework, MISP threat sharing, or cyber intelligence platforms
- Experience with cloud platforms such as AWS or Azure
- Ability to obtain a Secret clearance
- Bachelor's degree
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
- recognition awards program
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