Machine Learning Engineer

Job Title :-AI/ML Security Engineer - Information Security

Job Location :- Toronto, ON

Hybrid -3 day onsite mandatory

Mandatory Skills

1. Must Have : Gen-AI , LLM security solution, ML, MLOps
2. 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