Job Summary: The Senior Machine Learning Engineer is responsible for deploying, integrating, monitoring, and operationalizing AI and machine learning solutions using modern MLOps practices.

This role focuses on creating scalable and reusable deployment patterns and tooling to ensure reliable transition of models from development to production across the enterprise in a hybrid work environment based in Toronto, ON.

Responsibilities: Create and train machine learning models using relevant data.

Analyze data to identify relationships between inputs and desired outputs.

Develop models aligned with business objectives and establish metrics to track their progress.

Design and develop machine learning and deep learning systems.

Conduct machine learning experiments and tests to validate model performance.

Implement appropriate machine learning algorithms based on problem requirements.

Manage resources including hardware, data, and personnel to meet project deadlines.

Explore and visualize data to understand distributions and identify potential deployment challenges.

Ensure data quality through cleaning and supervise data acquisition when necessary.

Define validation strategies and preprocessing/feature engineering workflows.

Collaborate effectively within a team workplace and manage client relationships.

Required Skills: Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, and MLOps.

Strong proficiency in Python, SQL, and machine learning engineering.

Experience with CI/CD pipelines, containerization, APIs, automation, and model deployment.

Deep understanding of ML algorithms including classification, regression, clustering, and feature engineering.

Expertise in model evaluation,



hyperparameter tuning, drift detection, retraining, and production troubleshooting.

Familiarity with tools such as Power BI, Power Automate, VSCode, Git, Jira, Azure ML Studio, and Databricks.

Solid background in statistics and computer programming.

Desired Skills: Experience with scalable AI solution design and automation for enterprise environments.

Knowledge of monitoring and observability best practices for deployed models.

Proven ability to manage competing priorities and meet deadlines effectively.

Experience in client relationship management within technical projects.

Exposure to public sector projects or environments.

Rated Criteria: Machine Learning Model Development and Deployment - 30 Points MLOps and Automation Expertise - 25 Points Python and Technical Programming Skills - 15 Points Data Analysis and Feature Engineering - 10 Points Monitoring, Troubleshooting, and Performance Optimization - 10 Points Team Collaboration and Project Management - 10 Points Total: 100 Points Deliverables: Production-ready machine learning models aligned with business goals.

Reusable deployment patterns, automation scripts, and monitoring solutions.

Documentation of model performance metrics and validation strategies.

Reports on data quality, preprocessing, and feature engineering processes.

Regular updates and communication with stakeholders and clients.

Must Haves: Proven experience with Azure Machine Learning and related Microsoft AI platforms.

Strong expertise in MLOps, CI/CD, containerization, and API integration.

Advanced Python programming and machine learning engineering skills.

Comprehensive understanding of ML algorithms, statistics, and production model management.

Public Sector Experience: Preferred

📌 Senior Machine Learning Engineer (Ontario)
🏢 vTech Solution
📍 Ontario