Senior AI Platform & MLOps Specialist
- Employment type
- Full-time · On-site
- Posted
- October 17, 2026
- Province
- Quebec (QC)
Hiring confidence: Sparse posting · 7/100
This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored
Job Overview
This role is based in Quebec. Schneider Electric is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in Quebec
Average salary for Senior AI Platform & MLOps Specialist in Quebec
We do not have a salary benchmark for this title in Quebec yet. The posting does not state a salary either.
NOC code
This posting has not been matched to a NOC 2021 unit group yet. Use the NOC finder to identify the code from the duties listed above.
Typical qualifications for Canadian employers
- Senior-level experience in MLOps or AI platform engineering
- Experience building platform infrastructure for AI solutions
- Knowledge of cloud, on-premises, edge, and disconnected environments
- Understanding of model development and deployment lifecycle
- Experience with observability and governance systems
Fit check
Is this role right for you?
Top skills this posting asks for:
- MLOps
- AI Platform Engineering
- Infrastructure as Code
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What you'll do
- Build platform foundations for AI solutions in production
- Create infrastructure and automation for model development, evaluation, and release
- Implement observability and governance across AI systems
- Develop deployment capabilities for cloud, on-premises, edge, and disconnected environments
- Design reusable, self-service platform capabilities for AI engineers and product teams
- Operate and maintain production AI systems
- Embed within the AI team to support AI initiatives
What you'll need
- Senior-level experience in MLOps or AI platform engineering
- Experience building platform infrastructure for AI solutions
- Knowledge of cloud, on-premises, edge, and disconnected environments
- Understanding of model development and deployment lifecycle
- Experience with observability and governance systems
- Self-service platform capability development experience