Machine Learning Engineer

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