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Added 2 days ago
G
Chef d’équipe / Team Lead, Machine Learning & Computer Vision
Genetec
Montreal, QC
- Full-time
Added 2 days ago
G
Chef d’équipe / Team Lead, Machine Learning & Computer Vision
Genetec
Remote, Canada
- Full-time
- Remote
Added 2 days ago
IS
MLOPS/AI Lead
Iris Software Inc.
Toronto, ON
- Contract
Iris’s leading financial client is looking for MLOPS/AI Lead to join their team at Toronto, ON(Hybrid) location.
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
…Microsoft Foundry/Azure AI Foundry, Machine Learning Operations (MLOps), CI/CD, containers, APIs, automation, model deployment, monitoring, and observability. The ideal candidate will have…
Added 2 days ago
AF
Principal, AI Agent Control & Governance
ATB Financial
Calgary, AB
- Full-time
…governance requirements directly into technical workflows, MLOps pipelines, and agent execution environments. This ensures innovation velocity is maximized while maintaining audit-ready…
Added 2 days ago
SM
RQ00245 – Machine Learning Engineer – Senior
S M Software Solutions Inc
Toronto, ON
- Full-time
…Microsoft Foundry/Azure AI Foundry, Machine Learning Operations (MLOps), CI/CD, containers, APIs, automation, model deployment, monitoring, and observability. The ideal candidate will have…
Added 2 days ago
M
Senior Machine Learning Engineer / Applied Scientist
Microsoft
Vancouver, BC
- Full-time
Contribute to MLOps (data pipelines, telemetry, regression testing, monitoring).
Added 2 days ago
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Sr Spec, IT
Vale
Canada
- Full-time
We are seeking a Sr. Specialist, AI/Machine Learning Developer to join our AI & Automation Centre of Excellence for a permanent opportunity within Information Technology in Sudbury, ON.…
Added 2 days ago
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Sr AI Engineer
Nutrien
Saskatoon, SK
- Full-time
Implement MLOps and deployment standards - CI/CD for AI, model monitoring, retraining, version and lifecycle management - in partnership with AI Platforms & Operations
Added 2 days ago
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Sr AI Engineer
Nutrien
Calgary, AB
- Full-time
Implement MLOps and deployment standards - CI/CD for AI, model monitoring, retraining, version and lifecycle management - in partnership with AI Platforms & Operations
Added 2 days ago
S
AI Risk Management & AI Risk Engineering Consultant
Slalom
Toronto, ON · Greater Toronto Area, Canada
- Full-time
· MLOps or LLMOps experience, including CI/CD for models and agents, model and prompt registries, versioned rollout and production monitoring.
Added 2 days ago
AC
Manager, Data and AI - AI Systems Integrations and Agentic technical owner
Air Canada
Toronto, ON · Dorval, QC
- Full-time
Drive approved infrastructure-as-code, CI/CD, MLOps and LLMOps patterns, including application and model promotion, versioning, rollback and environment management.
Added 2 days ago
GT
Business Analyst - Credit Cards Product Analytics & Insight
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- Contract
…deploy machine learning models and AI solutions using modern MLOps practices, ensuring scalability, reliability, and continuous improvement of analytical…
Added 2 days ago
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AI Developer Test Management
Ericsson
Ottawa, ON
- Full-time
…delivery, strengthen software quality, and create a better developer…
Added 3 days ago
D
AWS AI Solution Architect
DEDICATTED
Canada
- Full-time
Understanding of MLOps / LLMOps practices and production AI lifecycle management.
Added 3 days ago
RT
Machine Learning Engineer
Russell Tobin
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 3 days ago
VS
Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 3 days ago
ES
Data Architect (Snowflake, DBT & AWS Focused)
Enterprise Solutions Inc.
Markham, ON
- Contract
Experience in Designing Streamlit apps and define new capabilities and data products leveraging snowflake ML and MLOPS capabilities
Added 3 days ago
TB
Forward Deployed AI Engineer
Type B Digital
Calgary, AB
- Full-time
Deployment experience on at least one major cloud (Azure, AWS or GCP), plus Docker, CI/CD and basic MLOps or LLMOps.
Added 3 days ago
BC
AI Engineer
BDO Canada
Toronto, ON
- Full-time
Practical experience with DevOps and MLOps practices, including Docker, Kubernetes, and CI/CD pipelines for machine learning workloads.
Added 3 days ago
AI
Senior Forward Deployed AI Engineer (Python, Data & GenAI)
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
Implement MLOps/LLMOps capabilities, including lifecycle management, CI/CD, MLflow, monitoring, deployment automation, rollback, and production support.
Added 3 days ago
B
Senior Databricks Data Platform Engineer
Brillio
Canada
- Contract
…and you will measure your success in platform reliability, developer productivity, and dollars…
Added 3 days ago
VS
Senior Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
…operationalize AI and machine-learning solutions using modern MLOps practices. The role will establish reusable deployment patterns, tooling, monitoring, and automation that enable AI…
Added 3 days ago
AI
Data & Analytics Leader - BFSI, AI Transformation
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
Knowledge of AI, machine learning, Generative AI, Agentic AI, MLOps/LLMOps, responsible AI, and AI-led business transformation.
Added 3 days ago
T
Senior Machine Learning Engineer
TEEMA
Toronto, ON
- Contract
Advanced hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, model deployment, monitoring and observability.

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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