Senior ML Engineer (Azure MLOps)

* Contract * Hybrid (Toronto, Ontario) * Posted on November 4, 2026 **Tri-global Solutions Group Inc.** **SENIOR MACHINE LEARNING ENGINEER (Azure MLOps; Enterprise AI & Data Centre of Excellence)** **Requisition #:** R26-3632 (RQ00245) **Location:** Hybrid (3 days onsite / 2 days WFH; Toronto, ON – \*See Work Model) **Engagement Type:** Contract **Number of Resources required:** 1 **Term:** 2026-11-23 to 2027-05-23 (130 days) with possible extension **Rate (CAD):** Up to $80.00 per hour / Commensurate with related experience and market competitiveness **Hours per day:** 7.25 **Security Screening:** Standard (Criminal Record Check) ———————————————————————— Tri-global Solutions Group Inc. is seeking one (1) Senior Machine Learning Engineer to join our talented Service Delivery team within Metrolinx. ***WORK MODEL:*** *The successful contractor will be working hybrid with 3 days in office at 277 Front Street West, Toronto, Ontario and 2 days remote/work from home per week.* Please review the project overview, description of services, and requirements below. If you meet the requirements and are interested in submitting for this role, please reply to this job posting. If you know other consultants who may be interested in this opportunity kindly share this job posting. Thank you. Tri-global Solutions Group Inc. Website: https://tri-global.com ———————————————————————— **PROJECT OVERVIEW** 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. **DESCRIPTION OF SERVICES** Responsibilities: – Creates machine learning models and utilizes data to train models – Focuses on analyzing data to find relations between the input and the desired output – Understands business objectives and develops models that help achieve them, along with metrics to track their progress – Designs and develops machine learning and deep learning systems – Runs machine learning tests and experiments – Implements appropriate machine learning algorithms **QUALIFICATIONS & EXPERIENCE** – Experience managing available resources such as hardware, data, and personnel so that deadlines are met – Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability – Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world – Experience verifying data quality, and/or ensuring it via data cleaning – Experience supervising the data acquisition process if more data is needed – Experience finding available datasets online that could be used