Define and architect MLOps capabilities and AI tools to support Canada’s cross-segment initiatives and ensure scalability and reuse
Design solutions that enable model development, deployment, and monitoring across multiple use cases
Establish best practices for model validation, performance monitoring, and lifecycle management
Co-design solutions with global AI teams, IT, and data teams to align with enterprise standards and leverage shared platforms
Drive R&D for advanced AI capabilities, ensuring integration with modern cloud-based platforms and data assets
Act as the subject matter expert for MLOps, guiding teams on automation, CI/CD for ML, and operationalization of AI models

Requirements

8+ years of experience in Data Science, Machine Learning, or AI Engineering, with a strong focus on MLOps and solution architecture
Proven track record in designing and implementing scalable ML pipelines and platforms in enterprise environments
Expertise in model development, validation, and deployment using modern cloud technologies and MLOps frameworks
Strong understanding of data assets, platforms, and advanced analytics concepts
Ability to lead cross-functional initiatives and collaborate with global teams
Excellent communication skills to influence technical and business stakeholders
Master’s degree or equivalent experience in Computer Science, Data Science, Engineering, or related quantitative fields

Benefits

health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage
adoption/surrogacy and wellness benefits
employee/family assistance plans
retirement savings plans (including pension and a global share ownership plan with employer matching contributions)
financial education and counseling resources
generous paid time off program in Canada includes holidays, vacation, personal, and sick days
full range of statutory leaves of absence

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

MLOpsAI toolsmodel developmentmodel validationperformance monitoringlifecycle managementCI/CD for MLscalable ML pipelinessolution architectureadvanced analytics

Soft Skills

leadershipcollaborationcommunicationinfluencecross-functional initiative management

Certifications

Master’s degree in Computer ScienceMaster’s degree in Data ScienceMaster’s degree in Engineering