Build reliable AI production systems with Azure Machine Learning, MLOps, and Python in a hybrid schedule requiring three onsite days weekly. This senior engineering role connects experimentation with scalable deployment. The Senior Machine Learning Engineer deploys, integrates, monitors, and operationalizes AI and machine-learning solutions. You will create reusable deployment patterns, tooling, monitoring, and automation for enterprise scale. The work includes model development, data analysis, experiments, and production troubleshooting. Key Responsibilities:

Deploy, integrate, monitor, and operationalize machine-learning solutions Create reusable deployment patterns, tooling, monitoring,



and automation Develop models and use data for training Define metrics supporting business objectives and model progress Run machine-learning tests and experiments Requirements:

Advanced Azure Machine Learning and Microsoft Foundry experience Hands-on MLOps, CI/CD, containers, APIs, and automation experience Robust Python, machine-learning engineering, and statistics skills Experience with model deployment, monitoring, observability, and troubleshooting Experience using Azure, Databricks, SQL, Git, and Power BI Apply senior machine-learning engineering expertise across Azure MLOps, Python, deployment, monitoring, and production model operations.

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📌 Senior Azure MLOps Engineer (Toronto)
🏢 FlexStaf IT
📍 Toronto