AI/ML Cybersecurity Engineer

Job Title: AI/ML Cybersecurity Engineer
Location: Chicago, IL 60131
Duration: Contract / Full time
About the Role:
We are seeking a highly skilled and innovative AI/ML Cybersecurity Engineer to join our growing security team. In this role, you will leverage artificial intelligence and machine learning to enhance threat detection, automate response systems, and build intelligent security frameworks that scale with evolving cyber threats. You will collaborate with security analysts, data scientists, and DevOps teams to develop and deploy AI-driven solutions that protect enterprise infrastructure, data, and applications.
Key Responsibilities:
Design, develop, and implement machine learning models to detect cybersecurity threats (e.g., malware, phishing, intrusion, APTs).
Analyze large datasets from logs, endpoints, and network traffic to identify patterns and anomalies.
Automate threat detection and response workflows using AI/ML models and tools.
Collaborate with SOC teams to improve detection rules and enrich incident response with intelligent analytics.
Develop models for behavior analytics (UEBA) to profile users and entities for early threat identification.
Integrate AI/ML models into existing SIEM, SOAR, or XDR platforms.
Stay updated on current threat landscapes and evaluate new AI techniques applicable to cybersecurity.
Ensure AI systems are explainable, auditable, and comply with data privacy and security standards.
Participate in red teaming and simulation exercises to validate model effectiveness.
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Cybersecurity, Data Science, or related field.
3+ years of experience in cybersecurity engineering or threat detection.
2+ years of hands-on experience with machine learning and data science in a security context.
Proficient in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn.
Strong understanding of security operations, threat intelligence, malware analysis, and SOC workflows.
Experience working with log analysis tools, SIEM platforms (e.g., Splunk, Elastic), and data lakes.
Solid understanding of networking, operating systems (Linux, Windows), and common attack vectors.
Preferred Qualifications:
Experience with NLP techniques applied to phishing and email threat detection.
Familiarity with cloud security (AWS, Azure, GCP) and security automation tools (e.g., SOAR).
Knowledge of adversarial machine learning and model robustness testing.
Security certifications such as CISSP, CEH, OSCP, or GIAC are a plus.