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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

machine learningcyber threat huntingmodel performance observabilityPythonMLOpsDockerKubernetesSIEM technologiesAWSAzure

intellectual curiosity

Secret clearance