Cybersecurity AI/ML Engineer

Role Overview

• Develop, deploy, monitor, tune, evaluate, report and maintain systems and procedures
• Identify and mitigate threats to the corporate network, corporate assets, and corporate users
• Identify core requirements, design, and implement security technologies
• Work with stakeholders to perform ongoing tuning and alerting on security technologies
• Incorporate advanced AI and machine learning methodologies into cybersecurity data
• Transform cybersecurity data into scalable detection capabilities
• Enhance analytics and improve threat detection under complex and adversarial conditions
• Prepare technical requirements and standards
• Assist in the identification, engineering and designing of security technologies including Security Incident and Event Managers (SIEM) and threat intelligence solutions
• Perform analysis of system logs to identify unauthorized use or access
• Create, analyze and communicate security metrics to leadership
• Participate in emergency response and security incident activities
• Recommend and evaluate security tools to identify more efficient and effective security measures
• Develop and deploy machine learning models for threat detection (anomaly detection, classification)
• Build feature engineering pipelines from security telemetry (logs, endpoint, network data)
• Implement and manage ML model training, experimentation and tuning workflows
• Deploy ML models using containerized environments (Docker, Kubernetes)
• Monitor model performance, drift and detection accuracy in production
• Apply AI-driven insights to threat hunting and incident response
• Collaborate with engineering and infrastructure teams to support scalable ML-enabled security systems

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 imp subnetting
• High level understanding of technology 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
• Ability to translate ambiguous cybersecurity problems into measurable analytical solutions
• 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
• 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
• Foster open communication, speaks with impact, listens to others and writes effectively
• Ability to effectively negotiate with vendors on upgrades and acquisitions
• Effective planning, time management, negotiation and delegation skills
• Expert level IT security processes and controls knowledge as well as IT infrastructure and networking technical knowledge
• Ability to approach problems with an open-mind and create new and innovative ideas and methods
• Advanced technical writing
• Experience in documentation tools such as Visio and Microsoft Office products
• Advanced information security standards/frameworks (i.e., NIST Cybersecurity Framework, ISO 27001) skills
• Advanced experience with Network and VLAN segmentation
• Strong analytical skills
• Ability to approach problems with an open-mind, use existing information and resources
• Creative, innovative, problem-solving and maximizing your potential to solve problems and improve methods
• Think positively when faced with obstacles, build on others ideas, think logically and intuitively
• Detailed oriented
• 1-5 years of experience in large and complex business environments with a successful track record working directly with senior level management preferred
• 1-5 years of experience in one or more of the following domains: Cybersecurity, Information Security, Data Science or related field.
• 1-3 years of experience with developing or supporting machine learning models in a security context preferred.
• High School Diploma or equivalent required
• Bachelor’s Degree in Cybersecurity, Computer Science, Data Science or related field or equivalent work experience strongly preferred.
• One or more security related certifications, such as CISSP, CCNP-Security, GIAC, CEH, or CPTS highly preferred
• AI/ML certifications are a plus.

Tech Stack

• Cyber Security
• DNS
• Docker
• ITSM
• Kubernetes
• Pandas
• PySpark
• Python
• Scikit-Learn
• Switching
• TCP/IP

Benefits

• Generous benefits package available on day one to include: 401K matching
• bonding leave for new parents (12 weeks, 100% paid)
• tuition assistance
• training
• GM employee auto discount
• community service pay
• nine company holidays