MLOps – Machine Learning Operations & Support

MLOps - Machine Learning Operations & Support

Possible 3 Month CTH Role Name: MLOPs_EG CO1 Work Site: Calgary, CA (Onsite) Start Date: Immediate Availability

Role Summary

We are seeking an experienced MLOps professional to provide end-to-end operational support for Machine Learning workloads across Azure and Databricks . The role will focus on ensuring the availability, scalability, reliability, security, and performance of ML pipelines and infrastructure.

Key Responsibilities

• Provide operational support for ML workloads across Azure and Databricks , ensuring platform availability and reliability.
• Manage and monitor Azure ML services, Databricks clusters, and cloud infrastructure .
• Support ML model deployment and versioning using CI/CD, MLflow, Azure DevOps, and containerized environments .
• Troubleshoot issues across the ML lifecycle, including: Data ingestion
• Model training
• Model serving
• Batch inference

Implement observability using Azure Monitor, Log Analytics, and Datadog for monitoring, metrics, logs, and alerts.

Enforce security and compliance standards, including access controls, key/certificate management, and secure data handling.

Optimize ML infrastructure performance and cost through compute management, job scheduling, auto-scaling, and cluster right-sizing.

Automate operational tasks using PowerShell, Bash, and Python .

Collaborate with data scientists and ML engineers to support production model integration.

Maintain operational runbooks, SOPs, incident reports, and knowledge-transfer documentation .

Required Skills

• Strong experience with MLOps and ML platform operations .
• Hands-on experience with Azure ML and Databricks .
• Experience with MLflow, Azure DevOps, CI/CD, and containerized environments .
• Strong troubleshooting experience across ML pipelines and infrastructure.
• Experience with Azure Monitor, Log Analytics, and/or Datadog .
• Knowledge of ML security, access control, certificates, and secure data handling.
• Strong scripting skills with PowerShell, Bash, and Python .
• Experience with cloud infrastructure optimization, auto-scaling, scheduling, and cost management.
• Strong collaboration and communication skills with technical and data science teams.