Job Title :-AI/ML Security Engineer - Information Security
Job Location :- Toronto, ON
Hybrid -3 day onsite mandatory
Mandatory Skills
- Must Have : Gen-AI , LLM security solution, ML, MLOps
- Good to have : Cloud Architecture, Cryptography
Primary Responsibilities:
o Identify, analyze, and benchmark Generative Al augmented, LLM agentic security solutions in the market.
o Conduct proof-of-concept (PoC) assessments of selected cybersecurity capabilities to validate effectiveness in real-world environments.
o Define security control baselines and evaluation criteria for emerging risk security solutions.
o Evaluate vendor claims, solution architecture, and technical scalability.
o secunity testing of GenAI-powered cybersecurity tools.
o Publish detailed reports on the security, compliance, and efficacy of evaluated products.
o Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems.
o Evaluate and assess open-source Al security libraries to build into enterprise AI stress testing and audit capabilities.
o Implement secure model development life cycle practices with automated white box and black box assessments for AI/ML models.
o Consistently enable strong developer and customer experience when liaising with application teams. Uphold Blue Box values when liaising with application teams.
Minimum Qualifications:
o Bachelor's Degree in Data Science, Statistics, Computer Science or Software Engineering
o 2- years' experience with Machine Learning Application Development
o 3+ years of software engineering experience
Preferred Qualifications:
o Master's Degree - Data Science, Statistics, Computer Science, or Software Engineering
o Machine Learning Operation Professional Certifications
o Demonstrated peer reviewed journal publications, conference presentations, open-source contributions, or similar activities.
o Strong knowledge of Adversarial Robustness techniques and tools for machine learning
o Strong knowledge of AI Risk Management frameworks and Trustworthy Al practices.
o Hands-on experience with applying statistics, machine leaming algorithms (DNN. NLP), big data, and data science toolkits. Hands-on experience designing, implementing. and operationalizing high performant AI/ML pipelines and writing production code
o Hands-on experience with deploying and operationalizing AIML models to public cloud environments.
o Hands-on experience evaluating open-source MIL tools, frameworks, and libraries.
o Hands-on experience with commonly used data science programming languages, packages, and tools.
o Hands-on experience with MLOps. DevOps. DataOps and API integrations.
o Hands-on experience with Al workload management.
• Hands-on experience with Cloud architecture design, implementation, and operations.
o Knowledge of application security controls (Web, API, Mobile, AL).
o Knowledge of security domains. common information security management and application frameworks: NIST 800-53, CSF. OWASP ASS.
o Knowledge of Secure SDLC, Application Security design and DevSecOps
o Full stack knowledge of application architectures including: Single Page Applications, REST APIs, SOAP APIs. Mobile Applications.
o Experience with Java, Javascript and mobile application development.
o Knowledge or familiarity with database architectures including Oracle, SQL. DB2 and NoSQL Databases
o Experience with Cloud security, architecture, design, implementation, and operations
o Exposure to IAM Controls (Auth 2.0, OIDC, JWI)
o Strong familiarity with Cryptography Controls (Data at rest, in motion).
Certifications - CISSP. CISM. CSSLP, CISA. CRISC
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