RQ00245 – Machine Learning Engineer – Senior

Job summary

Design, develop, deploy, integrate, monitor, and operationalize machine-learning and AI solutions using modern MLOps practices. Establish reusable deployment patterns, tools, monitoring, and automation to move models reliably into production and support enterprise-scale solutions.

Job details

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. How to Apply If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST. Mandatory Documents Updated Resume in Word format (Mandatory) Skills Matrix and References (Mandatory) Expected Hourly Rate (Mandatory) Visa Status (Mandatory) LinkedIn ID (Mandatory) Please note that we cannot proceed with your submission without the following mandatory documents. WhatsApp Group For daily job updates, you can also join our WhatsApp group using the link below: WhatsApp Group Link: Join our WhatsApp Group Email is the best way to reach us. You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.

What you’ll do

Design, develop, deploy, integrate, monitor, and operationalize machine-learning and AI solutions using modern MLOps practices. Establish reusable deployment patterns, tools, monitoring, and automation to move models reliably into production and support enterprise-scale solutions.

Requirements

Requires advanced hands-on experience with Azure Machine Learning or Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, deployment, monitoring, and observability, along with strong Python and machine-learning engineering skills. Candidates should understand machine-learning algorithms and statistics and have experience preparing data, engineering features, validating and evaluating models, and troubleshooting production systems.

Listed skills

• Python · Preferred
• Machine learning · Preferred
• CI/CD · Preferred
• SQL · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Azure Machine Learning
• Azure AI Foundry
• MLOps
• Python
• Machine Learning
• CI/CD
• Containerization
• API Integration
• Model Deployment
• Model Monitoring
• Observability
• SQL
• Databricks
• Feature Engineering
• Model Evaluation
• Statistics

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Government & Public Sector

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