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Added 2 days ago
MC
Senior Embedded Software Firmware Engineer (35835)
Myticas Consulting
Ottawa, ON
- Contract
We are seeking a Senior Embedded Software/Firmware Engineer to develop and test next-generation firmware for advanced embedded optical systems. This is a one-year contract based in Ottawa,…
Added 2 days ago
MC
Staff Embedded Software Firmware Engineer (35836)
Myticas Consulting
Ottawa, ON
- Contract
We are seeking a Staff Embedded Software/Firmware Engineer to design, develop, and test mission-critical firmware components for advanced embedded optical systems. This is a one-year…
Added 2 days ago
MC
Principal Embedded Software Firmware Engineer (35837)
Myticas Consulting
Ottawa, ON
- Contract
Principal Embedded Software/Firmware Engineer
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MC
Network Management System Developer (35520)
Myticas Consulting
Ottawa, ON
- Full-time
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Added 2 days ago
VS
Senior Machine Learning Engineer
vTech Solution Canada
Toronto, ON
- Contract
Added 2 days ago
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Ottawa, ON
- Full-time
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- $144,000 to $194,400 CAD / year
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Vancouver, BC · VCH | Vancouver General Hospital - Blusson Spinal Cord Centre (VGHBSC)
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Added 2 days ago
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Intern Bachelors Embedded Eng
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Ottawa, ON · Kanata, ON
- Full-time
The successful candidate will join the Honeywell Aerospace SATCOM Software Development Team as an Embedded Engineer Intern. In this role, the primary responsibility will be to develop…
Added 2 days ago
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Intern Bachelors Systems Eng
Honeywell Aerospace
Ottawa, ON · Kanata, ON
- Full-time
…this role, the primary responsibility will be to integrate software on hardware, create verification procedures to cover systems or software requirements, execute and report on those…
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vTech Solution Canada

Senior Machine Learning Engineer

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

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, deploy, integrate, monitor, and operationalize machine-learning solutions, establishing reusable MLOps patterns and automation to move models reliably into production. Analyze data, design and test models, and track their performance to support business objectives and enterprise-scale deployment.

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 and statistics, production model troubleshooting, and experience with data preparation, validation, evaluation, tuning, drift, and retraining; public-sector experience is preferred but not required.

Skills

Python
Machine Learning
MLOps
Azure Machine Learning
Azure AI Foundry
CI/CD
Model Deployment
Model Monitoring
Containers
APIs
Automation
SQL
Databricks
Statistics
Feature Engineering
Model Evaluation

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
Classification
Regression
Clustering
Feature Engineering
Model Evaluation
Hyperparameter Tuning
Data Cleaning
Data Visualization
Model Drift
Model Retraining

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