Azure Machine Learning and MLOps expertise define this contract role in Toronto. Work hybrid, with three onsite days weekly, from experimentation through production.

This Machine Learning Engineer contract runs from November 23, 2026, through May 23, 2027. The role requires Python, Azure Machine Learning, Microsoft Foundry, and reliable production engineering. You will work with CI/CD, containers, APIs, automation, deployment, monitoring, and observability.

Key Responsibilities:

- Move machine learning models from experimentation into production environments
- Build CI/CD, container, API, and automation workflows
- Deploy, monitor, and troubleshoot production machine learning models
- Manage model drift, retraining, and performance optimization




- Apply classification, regression, clustering, and feature engineering

Requirements:

- Advanced hands-on Azure Machine Learning and Microsoft Foundry experience
- Advanced MLOps experience with deployment and observability
- Robust Python and machine learning engineering skills
- Experience with SQL, Power BI, Databricks, Git, and Jira
- Understanding of statistical methods and model evaluation

Apply Azure, Python, and MLOps expertise to production machine learning engineering in Toronto’s hybrid contract environment.

📌 Azure Machine Learning Engineer (Toronto)
🏢 Bevertec
📍 Toronto