RQ00245 – Machine Learning Engineer – Senior

S M Software Solutions Inc; Toronto; Hybrid; CAD 110.000 - 160.000; Vollzeit

Zusammenfassung

Metrolinx is seeking a Senior Machine Learning Engineer to deploy and operationalize AI solutions using modern MLOps practices in a hybrid environment at 277 Front Street West, Toronto.

The role focuses on developing reusable deployment patterns, monitoring, and automation to scale enterprise AI. Candidates should have deep Python and ML engineering expertise and experience moving models from experimentation to production.

Qualifikationen

• Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, model deployment, monitoring, and observability.
• Strong Python and machine-learning engineering skills, with demonstrated experience taking models from experimentation into reliable production environments.
• Experience with Python, SQL, Power BI, Power Automate, VS Code, Git, Jira, Azure ML Studio, AI Foundry, Databricks.

Aufgaben

• Deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices.
• Establish reusable deployment patterns, tooling, monitoring, and automation.
• Enable AI solutions to move reliably from development into production and scale across the enterprise.
• Create machine-learning models and utilize data to train models.
• Focus on analysing data to find relationships between the input and the desired output.
• Understand business objectives and develop models that help achieve them, along with metrics to track their progress.
• Design and develop machine-learning and deep-learning systems.
• Run machine-learning tests and experiments.
• Implement appropriate machine-learning algorithms.

Kenntnisse

Python

Machine-learning engineering

Data analysis

Team collaboration

Observability

Tools

Azure ML Studio

Azure AI Foundry

MLOps

CI/CD

Containers

APIs

Databricks

SQL

Power BI

Power Automate

VS Code

Git

Jira

Jobbeschreibung

Client: Metrolinx – RQ00245

We are seeking a highly skilled Senior Machine Learning Engineer with advanced hands-on experience in Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, Machine Learning Operations (MLOps), CI/CD, containers, APIs, automation, model deployment, monitoring, and observability. The ideal candidate will have strong Python and machine-learning engineering expertise, with a proven ability to take machine-learning models from experimentation through development and into reliable production environments. The successful candidate will design, develop, deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices, establishing reusable deployment patterns, tools, monitoring, and automation to support enterprise-scale AI solutions.

Role Snapshot

• Job Title: RQ00245 – Machine Learning Engineer – Senior
• Client: Metrolinx
• Work Location: 277 Front Street West, Toronto, Ontario, Canada
• Work Arrangement: Hybrid – 3 Days per Week Onsite
• Estimated Start Date: November 23, 2026
• Estimated End Date: May 23, 2027
• Business Days: 130.00
• Hours: 7.25 hours per day
• Public Sector Experience: Preferred but not required

Must Have

• Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, model deployment, monitoring, and observability.
• Strong Python and machine-learning engineering skills, with demonstrated experience taking models from experimentation into reliable production environments.
• Experience with the following technology stack:
  • Python
  • SQL
  • Power BI
  • Power Automate
  • Visual Studio Code (VS Code)
  • Git
  • Jira
  • Azure (ML Studio, AI Foundry)
  • Databricks
• Deep understanding of machine-learning algorithms and statistics, including:
  • Classification
  • Regression
  • Clustering
  • Feature Engineering
  • Model Evaluation
  • Hyperparameter Tuning
  • Model Drift
  • Model Retraining
  • Performance Optimization
  • Production Model Troubleshooting

Description

Senior Machine Learning Engineer

The Senior Machine Learning Engineer will deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI solutions to move reliably from development into production and scale across the enterprise.

Responsibilities

• Deploy, integrate, monitor, and operationalize AI and machine-learning solutions using modern MLOps practices.
• Establish reusable deployment patterns, tooling, monitoring, and automation.
• Enable AI solutions to move reliably from development into production and scale across the enterprise.
• Create machine-learning models and utilize data to train models.
• Focus on analysing data to find relationships between the input and the desired output.
• Understand business objectives and develop models that help achieve them, along with metrics to track their progress.
• Design and develop machine-learning and deep-learning systems.
• Run machine-learning tests and experiments.
• Implement appropriate machine-learning algorithms.

General Skills

• Experience managing available resources such as hardware, data, and personnel to ensure deadlines are met.
• Experience analysing machine-learning algorithms that could be used to solve a given problem and ranking them by their probability of success.
• Experience exploring and visualizing data to gain an understanding of it, and then identifying differences in data distribution that could affect performance when deploying the model in real-world environments.
• Experience verifying data quality and/or ensuring data quality through data cleaning.
• Experience supervising the data acquisition process when additional data is required.
• Experience finding available datasets online that could be used for training.
• Experience defining validation strategies.
• Experience defining the preprocessing or feature engineering to be performed on a given dataset.
• Background in statistics and computer programming.
• A team player with a track record of meeting deadlines, managing competing priorities, and demonstrating client relationship management experience.

Additional Information

• Work Location: 277 Front Street West, Toronto, Ontario, Canada.
• Work Arrangement: Hybrid.
• Onsite Requirement: 3 days per week onsite.
• Public Sector Experience: Preferred but not required.
• Contract Duration: November 23, 2026, to May 23, 2027.
• Working Hours: 7.25 hours per day.