Senior AI Platform & MLOps Architect (Multi-Env Deployments)

Schneider Electric; Montreal (administrative region); On-site; CAD 115,000 - 162,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Career development

Employee share ownership plan

Flexible work arrangements

Job summary

Schneider Electric Montréal-based team is building the platform foundations to bring AI solutions into production reliably. You’ll create infrastructure, automation, observability, and governance to develop, evaluate, release, deploy, and operate models across cloud, on-premises, edge, and disconnected environments.

Embedded within the AI team, you will work with architects, developers, cybersecurity, and responsible AI stakeholders to ensure secure, traceable model management and deployment.

Qualifications

• Experience deploying and operating ML/AI systems.
• Proficient in software development and automation.
• Knowledge of monitoring, reliability, security, and release practices.
• Familiarity with model packaging and artifact management.

Responsibilities

• Build and maintain automated pipelines for model development, evaluation, packaging, release, and deployment.
• Enable reliable model inference across cloud-hosted, containerized, on-premises, edge, and disconnected environments.
• Implement model registries, artifact management, lineage, versioning, and release controls to support traceability throughout the model lifecycle.
• Create reproducible development and evaluation environments that enable testing and validation.
• Establish monitoring for model quality, latency, availability, resource consumption, and cost.
• Automate security scanning, dependency management, testing, and policy enforcement across AI development and deployment workflows.
• Implement controlled processes for promoting models and prompts across development, test, and production environments.
• Support GPU and CPU inference workloads and optimize performance, resource utilization, and cost.
• Develop rollback, fallback, and incident-response mechanisms to support reliable product operations.
• Collaborate with cybersecurity and responsible AI stakeholders to incorporate security, governance, and responsible AI requirements into the platform.
• Develop reusable, self-service platform capabilities that enable AI engineers and product development teams to build, evaluate, and deploy AI solutions more efficiently.

Skills

Cloud platforms

Containers

Kubernetes

CI/CD

Infrastructure as code

ML systems

Software development

Automation

Monitoring

Reliability

Security

Release management

Model packaging

Inference services

Artifact management

Job description

Schneider Electric Montréal-based team is building the platform foundations to bring AI solutions into production reliably. You’ll create infrastructure, automation, observability, and governance to develop, evaluate, release, deploy, and operate models across cloud, on-premises, edge, and disconnected environments.

Embedded within the AI team, you will work with architects, developers, cybersecurity, and responsible AI stakeholders to ensure secure, traceable model management and deployment.