Summary
✨ AI‑Generated
Provide end-to-end operational support for machine-learning workloads across cloud and data-platform environments. You will manage ML infrastructure, model deployment and versioning, CI/CD pipelines, monitoring and observability, troubleshooting across the ML lifecycle, and security and access controls for production systems.
Highlights
End-to-end MLOps opportunity spanning cloud infrastructure, model deployment, monitoring, CI/CD, and production support. The role offers hands-on responsibility for reliable and scalable machine-learning workloads and modern cloud-based ML operations.
Description
Job Overview
We are seeking an experienced MLOps Engineer to provide end-to-end operational support for Machine Learning workloads across Microsoft Azure and Databricks.
The ideal candidate will have strong experience with ML infrastructure, model deployment, CI/CD, monitoring, cloud operations, and production support.
Key Responsibilities
Provide operational support for ML pipelines and infrastructure across Azure and Databricks, ensuring availability, scalability, 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, and batch inference.Implement monitoring and observability using Azure Monitor, Log Analytics, and Datadog.Ensure security, access control, key/certificate management, and secure data handling across ML environments.Optimize ML infrastructure for cost and performance, including compute resources, scheduling, auto-scaling, and cluster right-sizing.Automate operational and maintenance activities using PowerShell, Bash, and Python.Collaborate with Data Scientists and ML Engineers to support production model integration.Maintain runbooks, SOPs, incident reports, and operational documentation to support knowledge transfer and audit readiness.
Key Skills
Azure ML | Databricks | MLflow | Azure DevOps | CI/CD | Python | PowerShell | Bash | Azure Monitor | Log Analytics | Datadog | Docker/Containers | ML Model Deployment | Cloud Infrastructure | Monitoring & Observability | Security & Compliance
Immediate availability and Calgary onsite availability are required.
