AI/ML Security Specialist

Job Title: AI/ML Security Specialist Information Security

Location: Toronto, ON (Hybrid)

Duration / Term: Long-Term Contract

Job Description

We are seeking a highly skilled and forward-thinking AI/ML Security Specialist to evaluate, test, and implement security solutions for Generative AI, LLM agents, and machine learning ecosystems. This role will focus on benchmarking AI-augmented cybersecurity tools, conducting proof-of-concept assessments, and integrating robust security controls into MLOps pipelines. The ideal candidate will have hands-on experience in AI model security, adversarial robustness, and cloud-native AI deployments, with a strong foundation in application security, DevSecOps, and trustworthy AI frameworks.

Minimum Qualifications

• Bachelor s degree in Data Science, Statistics, Computer Science, or Software Engineering
• 2+ years of experience in machine learning application development
• 3+ years of software engineering experience
• Strong understanding of AI/ML pipelines, model lifecycle, and security testing

Preferred Qualifications

• Master s degree in a relevant field
• Certifications in MLOps, AI Security, or Cloud Security (e.g., CISSP, CISM, CSSLP, CRISC)
• Demonstrated contributions to peer-reviewed publications, open-source projects, or conference presentations
• Deep knowledge of adversarial robustness, AI risk management frameworks, and trustworthy AI practices
• Hands-on experience with DNN, NLP, big data, cloud-native AI deployments, and open-source ML tools
• Familiarity with DevOps, MLOps, DataOps, and API integrations
• Experience with application security controls, Secure SDLC, and DevSecOps
• Strong grasp of IAM controls (OAuth 2.0, OIDC, JWT) and cryptographic standards

Key Responsibilities

• Identify and benchmark Generative AI and LLM-based security solutions
• Conduct PoC assessments to validate cybersecurity tools in real-world environments
• Define security control baselines and evaluation criteria for emerging AI risks
• Perform white-box and black-box testing of AI/ML models
• Integrate robustness and vulnerability testing into MLOps ecosystems
• Evaluate and integrate open-source AI security libraries into enterprise platforms
• Collaborate with application teams to ensure secure and seamless developer experiences
• Publish detailed reports on security, compliance, and efficacy of evaluated tools
• Ensure alignment with frameworks such as NIST 800-53, OWASP ASVS, and Zero Trust principles

Key Skills

AI Security, ML Security, Generative AI, LLM Security, MLOps, Adversarial Robustness, Trustworthy AI, IAM, OAuth 2.0, JWT, Cryptography, Secure SDLC, DevSecOps, Cloud Security, AWS, Google Cloud Platform, NLP, DNN, Python, Java, API Security, Application Security, Risk Management Frameworks, CISSP, CISM, CSSLP, CRISC, Open-Source AI Tools, AI Model Testing, AI Compliance, Security Baselines

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