Machine Learning Engineer

Bevertec; Toronto; Hybrid; CAD 103,000 - 158,000; Full time

Job summary

Bevertec in Toronto is seeking a contract ML Engineer to drive end-to-end ML pipelines in production. This hybrid role requires three days on-site per week.

You will implement CI/CD, model deployment, monitoring, and observability, using Python, SQL, Azure ML Studio, Azure AI Foundry, Databricks, and Power BI.

Start date 2026-11-23; End date 2027-05-23. The role is based in Toronto with hybrid work arrangements.

Qualifications

• Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry (Azure AI Foundry), and MLOps, including CI/CD, containers, APIs, automation, model deployment, monitoring, and observability.
• Strong Python and Machine Learning Engineering skills, with demonstrated experience taking ML models from experimentation into reliable production environments.
• Experience with the following technology stack: Python, SQL, Power BI, Power Automate, VS Code, Git, Jira, Azure ML Studio, Azure AI Foundry, and Databricks.
• Deep understanding of Machine Learning algorithms and statistical methods, including classification, regression, clustering, and feature engineering.
• Experience with model evaluation, hyperparameter tuning, model drift, retraining, performance optimization, and production model troubleshooting.

Skills

Python

Machine Learning

ML Engineering

CI/CD

APIs

Automation

Model deployment

Monitoring

Observability

SQL

Power BI

Power Automate

VS Code

Git

Jira

Databricks

Azure ML Studio

Azure AI Foundry

Model evaluation

Hyperparameter tuning

Model drift

Retraining

Production troubleshooting

Feature engineering

Classification

Regression

Clustering

Tools

Azure ML Studio

Azure AI Foundry

Jira

VS Code

Git

Databricks

Power BI

Power Automate

Job description

Employment Type: Contract

Start Date: 2026-11-23

End Date: 2027-05-23

Location: Toronto

Work Arrangement: Hybrid – 3 days onsite per week

Must Haves:

• Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry (Azure AI Foundry), and MLOps, including CI/CD, containers, APIs, automation, model deployment, monitoring, and observability.
• Strong Python and Machine Learning Engineering skills, with demonstrated experience taking ML models from experimentation into reliable production environments.
• Experience with the following technology stack: Python, SQL, Power BI, Power Automate, VS Code, Git, Jira, Azure ML Studio, Azure AI Foundry, and Databricks.
• Deep understanding of Machine Learning algorithms and statistical methods, including classification, regression, clustering, and feature engineering.
• Experience with model evaluation, hyperparameter tuning, model drift, retraining, performance optimization, and production model troubleshooting.

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