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Senior DevOps/MLOps/Cloud Engineer

amyantek • Canada
Remote
This Job is No Longer Active This position is no longer accepting applications

We are seeking a highly skilled Senior DevOps/MLOps/Cloud Engineer to lead platform engineering, deployment automation, and AI/ML model deployment on Azure. This role emphasizes DevOps excellence, secure and cost-efficient deployments, and production-grade AI delivery, while supporting ML lifecycle management and scalable data engineering solutions.

Key Highlights
Lead platform engineering and deployment automation on Azure
Implement secure and cost-efficient deployments
Support ML lifecycle management and scalable data engineering solutions
Key Responsibilities
Design and implement robust CI/CD pipelines using Azure DevOps, Git, and YAML
Manage end-to-end deployment pipelines across Dev, QA, and Prod environments
Lead deployment of AI/ML models into production using automated pipelines
Technical Skills Required
Azure ecosystem (ADF, Databricks, ADLS, Azure SQL) CI/CD pipelines, Git, and YAML-based deployments Infrastructure as Code (ARM, Bicep, Terraform) SQL and relational databases (Azure SQL, Oracle) REST API development and integration
Benefits & Perks
8 month contract
Fully remote work
Toronto, Ontario location
Nice to Have
Experience with Azure AI Search and Azure AI Foundry
Experience with event-driven architecture (Event Grid, Service Bus)
Exposure to streaming platforms (Kafka, Event Hubs)

Job Description

WE'RE HIRING

Job Title: RQ00613 - Senior DevOps / MLOps / Cloud Engineer

8 month contract

Duration: 2026-04-13 - 2026-12-18

Work Status: Fully Remote

Location: Toronto, Ontario

Must-Have Skills:

  • 10+ years of experience designing and implementing CI/CD pipelines using Azure DevOps, Git, and YAML
  • 10+ years of experience deploying AI/ML models into production using automated pipelines
  • 10+ years of experience implementing ML lifecycle management (training, validation, deployment, monitoring)
  • 10+ years of experience designing and building data pipelines using Azure Data Factory, Databricks, and ADLS

Role Overview:

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