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BuzzClan

Senior Machine Learning Engineer

Toronto, ON, Canada

Contract

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Applications open in a new tab.

Job details

Job type: Contract
Apply by: Dec 4, 2026
Posting language: English
Posted: Nov 4, 2026

Original job description

Job Title: Machine Learning Engineer – Senior

Location: Toronto, ON (Hybrid – 3 Days Onsite)

Client: Public Sector

Duration: 6+ Months Contract (Possibility of Extension)

Required Experience and Skills

Extensive hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, and MLOps practices.
Strong proficiency in Python and SQL, with demonstrated experience developing, testing, and deploying machine learning models into production environments.
Experience implementing CI/CD pipelines, containers, APIs, automation, model deployment, monitoring, and observability.
Strong understanding of machine learning algorithms, including classification, regression, clustering, feature engineering, and model evaluation.
Experience with hyperparameter tuning, model optimization, performance troubleshooting, drift detection, and automated model retraining.
Hands-on experience with Azure ML Studio, Azure AI Foundry, Databricks, Git, VS Code, Jira, Power BI, and Power Automate.
Experience designing, developing, integrating, and operationalizing machine learning and deep learning solutions.
Strong knowledge of statistics, data preprocessing, data cleaning, feature engineering, and validation strategies.
Ability to analyze and visualize datasets, identify data distribution differences, and ensure data quality for reliable model performance.
Experience defining business objectives, developing appropriate ML solutions, and establishing performance metrics to measure outcomes.
Strong problem-solving, analytical, communication, and stakeholder management skills.
Ability to manage technical resources, competing priorities, and project deadlines while collaborating with cross-functional teams.

Nice-to-Have Skills and Experience

Previous public-sector or government experience.
Experience establishing reusable MLOps frameworks, deployment patterns, and enterprise-wide ML automation.
Experience with large-scale data processing using Azure Databricks and related cloud data platforms.
Experience with production model monitoring, observability, drift detection, and continuous improvement.
Familiarity with Power BI and Power Automate for analytics, reporting, and workflow automation.
Experience integrating ML solutions with enterprise applications through APIs and automated workflows.

If this aligns with your experience, please share your updated resume with me at Afzal.Khan@buzzclan.com.

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More about this job

Responsibilities

Design, develop, integrate, deploy, and operationalize machine learning and deep learning solutions in production, including CI/CD pipelines, automation, monitoring, and observability. Define business objectives and performance metrics, optimize and troubleshoot models, detect drift, and collaborate with stakeholders and cross-functional teams.

Requirements

Requires extensive hands-on experience with Azure Machine Learning, Azure AI Foundry, MLOps, Python, SQL, and production model development and deployment. Candidates should also have strong knowledge of machine learning methods, statistics, data preparation and validation, model optimization and monitoring, and the ability to manage priorities and communicate effectively.

Skills

Azure Machine Learning
Azure AI Foundry
MLOps
Python
SQL
Machine Learning
Deep Learning
CI/CD
Containers
APIs
Model Deployment
Model Monitoring
Azure Databricks
Feature Engineering
Power BI

Visa sponsorship

Not detected in the job text

Hiring contact

Afzal Khan

Hiring contact email

Afzal.Khan@buzzclan.com

Keywords

Azure Machine Learning
Microsoft Foundry
Azure AI Foundry
MLOps
Python
SQL
CI/CD Pipelines
Containers
APIs
Machine Learning Algorithms
Classification
Regression
Clustering
Feature Engineering
Model Evaluation
Hyperparameter Tuning
Model Optimization
Model Deployment
Model Monitoring
Observability
Drift Detection
Automated Model Retraining
Azure ML Studio
Databricks
Git
VS Code
Jira
Power BI
Power Automate
Data Preprocessing

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