Cybersecurity AI/ML Engineer - Hybrid, 4-Day Week

GM Financial; Arlington (TX); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

401(k) match

Tuition assistance

Employee discount

Job summary

GM Financial is seeking a Cybersecurity AI/ML Engineer to develop, deploy and monitor advanced threat detection systems, applying ML to transform security data into scalable protections and collaborating with engineering and infrastructure teams.

You will work in a flexible hybrid environment at Las Colinas, building ML models in Docker/Kubernetes, and contributing to anomaly detection, model tuning, and incident response as part of a high-impact security program.

Qualifications

• 1-5 years in large, complex environments with senior management exposure.
• Bachelor’s Degree in Cybersecurity, CS, Data Science or related field or equivalent work experience strongly preferred.
• Security certifications such as CISSP, CCNP-Security, GIAC, CEH, or CPTS are highly preferred.

Responsibilities

• Prepare technical requirements and standards.
• Design and evaluate security technologies including SIEM, IDS/IPS, endpoints, WAFs, cloud security, VPNs and firewalls.
• Develop and deploy ML models for threat detection and deploy in containerized environments (Docker, Kubernetes).
• Monitor model performance, drift and detection accuracy in production.
• Collaborate with engineering and infrastructure teams to support scalable ML-enabled security systems.

Skills

Networking concepts

Infrastructure design

ITSM

Python for ML

Machine learning

Anomaly detection

Statistical modeling

AI/LLMs

Threat detection

Security analytics

Education

Bachelor's degree

Tools

Visio

Microsoft Office

Pandas

scikit-learn

PySpark

Docker

Kubernetes

Job description

GM Financial is seeking a Cybersecurity AI/ML Engineer to develop, deploy and monitor advanced threat detection systems, applying ML to transform security data into scalable protections and collaborating with engineering and infrastructure teams.

You will work in a flexible hybrid environment at Las Colinas, building ML models in Docker/Kubernetes, and contributing to anomaly detection, model tuning, and incident response as part of a high-impact security program.