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AI/ ML Engineer - On Site MN, IL or NJ

LinkedIn UnitedHealth Group Plymouth, MN
Not Applicable Posted March 26, 2026 Job link
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Requirements
  • Security Analyst Foundation
  • Proven experience in cybersecurity, including threat detection, incident response, and vulnerability management
  • Familiarity with frameworks like NIST AI RMF, OWASP AI Security, and MITRE ATLAS
  • Certifications such as CISSP, CISA, or the new ISC2 Cybersecurity AI Certificate are highly recommended
  • AI & Machine Learning Expertise
  • Understanding of supervised, unsupervised, and reinforcement learning models
  • Experience with tools like TensorFlow, PyTorch, HuggingFace Transformers, and scikit-learn
  • Ability to assess AI model risks, bias, and explainability (XAI)
  • AI Security Specialization
  • Knowledge of adversarial AI threats, model inversion, data poisoning, and secure model lifecycle management
  • Familiarity with AI-specific security tools and workflows (e.g., AI UEBA, threat triage bots, Graph API consent automation)
  • Experience in red teaming and vulnerability testing for AI systems
  • Fast Learning & Adaptability
  • Ability to stay current with emerging threats and evolving AI technologies
  • Participation in ongoing training programs like the ESRO AI Security curriculum and AI persona development tracks
  • Communication & Collaboration
  • Solid written and verbal communication skills to articulate risks, mitigation strategies, and technical concepts to diverse stakeholders
  • Experience contributing to governance frameworks, OKRs, and cross-functional working sessions
  • 3+ years of experience delivering statistical models, machine learning (ML), or artificial intelligence (AI) solutions in a large organization
  • 3+ years of real-world data science experience in or supporting a large organization
  • 3+ years of real-world data engineering experience
  • Experience with Generative AI (GenAI)
  • Proven knowledge of adversarial AI threats, including model inversion, data poisoning, and secure model lifecycle management
  • Proven fluency in Python and SQL
  • Proven ability to stay current with emerging threats and evolving AI technologies
Preferred Skills
  • Security Analyst Foundation
  • Proven experience in cybersecurity, including threat detection, incident response, and vulnerability management
  • Familiarity with frameworks like NIST AI RMF, OWASP AI Security, and MITRE ATLAS
  • Certifications such as CISSP, CISA, or the new ISC2 Cybersecurity AI Certificate are highly recommended
  • Understanding of supervised, unsupervised, and reinforcement learning models
  • Experience in the cybersecurity domain, ideally as a Security Operations Center (SOC) analyst
  • Demonstrated familiarity with frameworks such as NIST AI Risk Management Framework (RMF), OWASP AI Security, or MITRE ATLAS
  • Customer-facing experience
  • Proven broad knowledge of information technology, including hardware, networking, architecture, protocols, file systems, and operating systems
  • Proficiency in data querying and reporting
  • Proven solid written and verbal communication skills to clearly articulate risks, mitigation strategies, and technical concepts to diverse stakeholders