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TekStaff IT Solutions

Machine Learning Engineer - Senior

Toronto, ON, Canada

Contract

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Job details

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

Original job description

TekStaff's Client has a current vacancy for " Machine Learning Engineer - Senior”

Job Description

This is a 6 month contract located in Toronto, ON (3 days onsite/2 days remote (subject to change).

Please note - This is a 7.25 hour work day.

*All successful candidates will be subject to a mandatory credit AND criminal check as per the client.

*Please note that all contractors are subject to a possible Holiday Leave program schedule, set by the client.

Job Details:

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: 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 General Skills: 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 for training Experience defining validation strategies Experience defining the preprocessing or feature engineering to be done on a given dataset Background in statistics and computer programming A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experience

Must Haves:

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. Tech stack: Python, SQL, Power BI, Power Automate, VSCode, Git, Jira, Azure (ML Studio, AI Foundry), Databricks.
Deep understanding of ML algorithms and statistics, including classification, regression, clustering, feature engineering, model evaluation, hyperparameter tuning, drift, retraining, performance optimization and production model troubleshooting.

TekStaff may use artificial intelligence (AI) tools as part of the applicant screening process. However, applications will also be reviewed by a member of our Recruitment team to ensure a fair and thorough assessment.

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More about this job

Responsibilities

Develop, deploy, integrate, and operationalize machine-learning solutions, establishing reusable MLOps patterns, tooling, monitoring, and automation to move models reliably into production. Design and test models, analyze and prepare data, evaluate performance, and support production scaling and troubleshooting.

Requirements

Requires advanced hands-on experience with Azure Machine Learning or Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, deployment, monitoring, and observability. Candidates should have strong Python and machine-learning engineering skills, deep knowledge of algorithms and statistics, and experience taking models from experimentation into production.

Skills

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

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Power BI
Power Automate
Visual Studio Code
Git
Jira
Azure Machine Learning
Azure AI Foundry
Databricks
MLOps
CI/CD
Containers
APIs
Automation
Model Deployment
Model Monitoring
Observability
Machine Learning
Deep Learning
Statistics
Classification
Regression
Clustering
Feature Engineering
Model Evaluation
Hyperparameter Tuning
Model Drift
Model Retraining
Performance Optimization

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