Cybersecurity AI/ML Engineer

6w1 month ago

GM Financial

Irving, US · Full-time · $135,000 – $155,000

About this role

This role develops, deploys, and maintains systems and procedures to identify and mitigate threats to corporate networks, assets, and users. It incorporates advanced AI and machine learning methodologies to transform cybersecurity data into scalable detection capabilities and improve threat detection under complex conditions.

Day-to-day tasks include preparing technical requirements, engineering security technologies like SIEM, IDS/IPS, and WAF, and performing system log analysis. You will also develop and deploy machine learning models for anomaly detection and classification, build feature engineering pipelines from telemetry, and monitor model performance in production.

You will join a mission-focused environment with specialized teams including Engineering, Threat Intelligence, and Incident Response. Cybersecurity has direct reporting lines to the CEO, ensuring your work is recognized and supported at the highest levels while enabling bold innovation and adoption of cutting-edge technologies.

This position offers the freedom to explore, the tools to build, and the support to thrive. You will shape the future of cybersecurity at GM Financial, working collaboratively to drive innovation across the environment.

Requirements

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
Strong working knowledge of Intel platforms, iSeries, and pSeries servers
Advanced understanding of IT Service Management (ITSM) best practices and processes
Experience with UML Design Tools
Advanced knowledge of TCP/IP, OSI model, and IP subnetting
High-level understanding of technology infrastructure, security concepts, and platforms

Responsibilities

Prepares technical requirements and standards
Assists in engineering security technologies including SIEM, IDS/IPS, WAF, cloud security, VPNs, and firewalls
Develops and deploys machine learning models for threat detection (anomaly detection, classification)
Builds 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)
Monitors model performance, drift, and detection accuracy in production
Applies AI-driven insights to threat hunting and incident response

Benefits

Exceptional leadership visibility with direct reporting lines to the CEO
Mission-focused environment with specialized teams including Engineering, Threat Intelligence, and Incident Response
Freedom to innovate and adopt cutting-edge technologies
Support to thrive with the tools to build and explore