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Querentia
MLOps – Machine Learning Operations & SupportQuerentia • Calgary, AB, Canada
MLOps – Machine Learning Operations & Support

MLOps – Machine Learning Operations & Support

Querentia • Calgary, AB, Canada
2 days ago
Job type
  • Full-time
  • Quick Apply
Job description

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.

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MLOps – Machine Learning Operations & Support • Calgary, AB, Canada

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