Cybersecurity AI_ML Engineer

Responsibilities

• Prepares technical requirements and standards
• Aids in the identification, engineering, and design of security technologies including, but not limited to: Security Incident and Event Managers (SIEM) and threat intelligence solutions, Intrusion Detection and Prevention Systems (IDS/IPS), Endpoint security solutions, Web Application Firewalls (WAF), Cloud Security, VPNs and Firewalls
• Performs analysis of system logs to identify unauthorized use or access
• Creates, analyzes, and communicates security metrics to leadership
• Participates in emergency response and security incident activities
• Recommends and evaluates security tools to identify more efficient and effective security measures
• Develops and deploys machine learning models for threat detection (anomaly detection, classification)
• Buils feature engineering pipelines from security telemetry (logs, endpoint, network data)
• Implements and manages ML model training, experimentation, and tuning workflows
• Deploys ML models using containerized environments (Docker, Kubernetes)
• Maintains model performance, drift, and detection accuracy in production
• Applies AI-driven insights to threat hunting and incident response
• Collaborates with engineering and infrastructure teams to support scalable ML-enabled security systems

Qualifications

• Strong knowledge of networking concepts, protocols, and infrastructure security
• Advanced knowledge in Infrastructure design and management
• Working knowledge of management processes such as personnel administration, planning, and budgeting
• Advanced understanding of IT Service Management (ITSM) best practices and processes
• Advanced knowledge of Intel platforms, iSeries and pSeries servers
• Advanced understanding of IT infrastructure, security concepts, and platforms
• Deep understanding of machine learning techniques including anomaly detection and statistical modeling
• Experience with unsupervised, semi-supervised, and advanced modeling approaches
• Strong foundation in probability, statistics, and data analysis
• Experience designing experiments, validation strategies, and evaluating model performance
• Expert-level Python for data science and machine learning (e.g., pandas, scikit-learn, PySpark)
• Experience with large-scale data processing and distributed data systems
• Understanding of adversarial ML concepts and model robustness (preferred)
• Experience with LLMs, deep learning, or AI-assisted detection (preferred)
• Demonstrated success in project management
• Advanced knowledge of the OSI model and security that is associated with each layer
• Strong understanding of routing and switching protocols as they relate to load balancing
• Strong understanding of application layer protocols including HTTP, SSH, SSL, and DNS
• Communicates quickly, clearly, concisely, appropriately, and intelligently
• Fosters open communication, speaks with impact, listens to others, and writes effectively
• Effective planning, time management, negotiation, and delegation skills
• Advanced technical writing
• Advanced information security standards/frameworks (i.e., NIST Cybersecurity Framework, ISO 27001) skills
• Advanced experience with Network and VLAN segmentation
• Strong analytical skills
• Detail-oriented