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Added 1 day ago
E
Manager, Investment Finance
Equiton
Burlington, ON
- Full-time
Added 1 day ago
VS
Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
Added 1 day ago
B
Sales Development Representative
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Mississauga, ON
- Full-time
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C
Product Manager
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Cavtera builds digital solutions that connect real-world operations with data, software, and decision-making. We work closely with clients to understand how their businesses operate on the…
Added 1 day ago
CL
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Toronto, ON · North York, ON
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Added 1 day ago
VH
Full Stack Engineer
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Markham, ON
- Full-time
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C
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Added 1 day ago
Ward Clerk
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Ward Clerk
Health Sciences North
Sudbury, ON
Added 1 day ago
Senior Business Analyst
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Winnipeg, MB · London, ON · Toronto, ON
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MI
Senior Manager, Fund Accounting, Private Markets
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- $105,000 to $154,000 CAD / year
- Full-time
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MI
Fund Accountant, Private Markets
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Toronto, ON
- $60,000 to $88,000 CAD / year
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VC
Client Service Associate (CSA) - Planning & Scheduling - Full-time
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Brantford, ON · Delhi, ON
- $20 to $21.25 CAD / hour
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Added 1 day ago
Project Engineer (Engineer 1-3) (Term) (Bible Hill)
The Government of Nova Scotia
Bible Hill, NS
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VE
Maintenance & Project Manager
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Pickering, ON
- Full-time
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UH
Registered Nurse - Progressive and Geriatric Rehabilitation Unit
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UH
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Toronto, ON
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UH
Registered Nurse - Progressive and Geriatric Rehabilitation Unit
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TI
Automation and Controls Engineer/Specialist
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High Prairie, AB
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MF
Director, Pod Owner
Mackenzie Financial Corporation
Toronto, ON · Greater Toronto Area, ON
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Added 1 day ago
UO
Information Officer (Over Night)
University of Ottawa
Ottawa, ON · Stanton Residence
- Full-time
Added 1 day ago
M
Senior Accountant
Millards
Brantford, ON
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Added 1 day ago
UO
Undergraduate Program Advising Officer
University of Victoria
Victoria, BC
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TI
Business Analyst
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Toronto, ON
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Added 1 day ago
MI
Senior Manager, Fund Accounting, Private Markets
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Vancouver, BC
- $105,000 to $154,000 CAD / year
- Full-time

vTech Solution Canada

Machine Learning Engineer

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 5, 2026
Posting language: English
Posted: Nov 5, 2026

Original job description

Job Title: Machine Learning Engineer - Senior

Location: Toronto, ON

Work Mode: Hybrid (3 days a week onsite)

Description

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.

Public Sector Experience: preferred but not required

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More about this job

Responsibilities

Develop, test, and deploy machine-learning and deep-learning models that address business objectives, using appropriate algorithms and measurable performance metrics. Establish reusable MLOps deployment patterns, automation, monitoring, and operational practices to move AI solutions reliably into production and scale them across the enterprise.

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 have deep knowledge of machine-learning algorithms, statistics, data preparation, model evaluation, tuning, drift, retraining, and production troubleshooting; public-sector experience is preferred but not required.

Skills

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

Visa sponsorship

Not detected in the job text

Keywords

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

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