Jobs in Canada

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Added 2 months ago
OA
Product Developer - OpenRoad Auto
OpenRoad Auto Group
Richmond, BC
- Full-time
Strong backend development experience with Node.js, .NET/C#, Python, or similar technologies.
Added 2 months ago
BI Developer - 1 Year Contract
Human Resources
Toronto, ON
Work Arrangement: Hybrid: 4 Days per Week On-Site
Added 3 months ago
TG
Senior Quality Assurance Engineer
TMX Group
Toronto, ON
- $65 to $85 CAD / hour
- Full-time
Must Have(s):
Added 2 months ago
Lead Software Developer
Geotab
Oakville, ON
As a Lead Software Developer your key area of responsibility will be designing, building and maintaining efficient, reusable, reliable code to develop high throughput, performance critical,…
Added 3 months ago
PS
Senior Developer, Private Markets Solutions Delivery
Public Sector Pension Investment Board
Montreal, QC
- Full-time
As a Senior Developer, Integration, you will design, develop and maintain robust, scalable integration solutions in close collaboration with our business partners. More specifically, you…
Added 2 months ago
W
Staff Systems Engineer - Safety Methodologies
Waabi
Toronto, ON
- $200,000 to $256,000 USD / year
- Full-time
Excellent scripting and data analysis skills (Python, SQL), and a solid foundation in statistics.
Added 2 months ago
Price, Promotion & Trade Analyst
Human Resources
Toronto, ON
Work Arrangement: Hybrid: 4 Days per Week On-Site
Added 5 months ago
T
Data Engineer
Tactable
Toronto, Ontario
- Full-time
Build scalable, reliable ETL/ELT pipelines using Python, and SQL
Added 5 months ago
A
Dynatrace Observability Consultant - Bilingual (FR)
Arctiq
Montreal, Quebec
- Full-time
Experience with database technologies (Oracle, DB2, MS SQL)
Added 5 months ago
B
Senior Data Engineer
BrainStation
Toronto, Ontario
- $120,000 to $145,000 CAD / year
- Full-time
Strong programming skills in SQL, Python, or related languages.
Added 3 months ago
MS
Senior Full Stack Engineer
Motorola Solutions
Vancouver, BC
- Full-time
7+ years of experience building backend systems using Node.js API frameworks (HapiJS preferred), with additional experience in Python a plus
Added 4 months ago
Production Support Analyst
mthree Recruiting Portal
Toronto, ON
What we’re looking for: (must have)
Added 3 months ago
DC
Manager: Post-Merger Integration
Dillon Consulting Limited
London, ON
- Full-time
This is a new position and can be based in our London ON office
Added 3 months ago
TG
Database Engineer
TMX Group
Toronto, ON
- Full-time
Job Location: Hybrid (2-3 days in office) - based in Toronto, ON · Must Have(s)
Added 2 months ago
MC
Senior Machine Learning Engineer Specialist – AI Centre of Excellence (35668)
Myticas Consulting
Canada
- Contract
The successful candidate will bring expert-level Python and SQL skills, combined with deep hands-on experience with Azure Machine Learning, Databricks, MLflow, CI/CD, MLOps, model…
Added 2 months ago
Senior Manager, Expense Oversight and Transparency
Scotiabank
Toronto, ON
Data Analytics experience using SQL and Python is highly desirable
Added 2 months ago
E
BI Dev/Ops Engineer, Sys Admin/Architect
eBay
Toronto, ON
- Full-time
Intermediate/Advanced knowledge & experience with SQL, Linux/Shell.
Added 5 months ago
L
Senior Specialist - Data Engineering
LTM
Toronto, Ontario
- $100,000 to $120,000 CAD / year
- Full-time
Proven experience as an ETL Developer Informatica PowerCenter and Informatica BDM
Added 6 months ago
PD
Remote Software Developer - Europe / South America
PAK digital
Remote, Canada
- $24,000 to $36,000 USD / year
- Contract
- Remote
You will work on web application development across the frontend and backend. The ideal developer has strong experience building production-ready applications, integrating APIs, working…
Added 6 months ago
C
Senior Software Engineer
Clutch
Toronto, Ontario
- $160,000 to $200,000 CAD / year
- Full-time
Experience with relational databases (PostgreSQL, MySQL, Oracle) and writing efficient SQL queries, schema design, and performance optimization
Added 2 months ago
SimCorp Dimension (SCD) Specialist
Munich Re
Toronto, ON
Experience in Cloud infrastructure (MS Azure), API usage is a plus (SQL, Python, JSON)
Added 3 months ago
OW
Oliver Wyman - Associate Team Leader; Team Leader; Director-Data and Analytics - Toronto
Oliver Wyman Group
Toronto, ON
- Other
Experience in using advanced analytics and data manipulation software - R, Python, SAS, SQL, or SPSS.
Added 4 months ago
Economist Intern
Government of Alberta
Edmonton, Alberta
The Economist Intern will work with considerable guidance given the lack of work experience. While they are expected to take the initiative on assignments, they will have support from…
Added 4 months ago
DD
Senior Software Engineer Fullstack
Dominion Dynamics
Ottawa, ON
- Full-time
…consequences. You'll shape the architecture, work directly with the CTO and our hardware and embedded teams, and see your work reach the field in days, not…
Added 2 months ago
A
Analyste BI senior
AtkinsRéalis
Montreal, QC
- Full-time
…clear, useful insights. As a Senior BI Analyst, you will work with project teams, business stakeholders and technology specialists to develop and improve business intelligence solutions for…

Myticas Consulting

Senior Machine Learning Engineer Specialist – AI Centre of Excellence (35668)

Canada

Contract

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Job details

Job type: Contract
Posting language: English
Posted: Sep 10, 2026

Original job description

Senior Machine Learning Engineer / Specialist – AI Centre of Excellence

Primary Focus: Machine Learning Engineering, MLOps & Production AI Solutions

Position Overview

We are seeking an experienced Senior Machine Learning Engineer / Specialist to support an enterprise AI Centre of Excellence (AI CoE) and its Machine Learning and Data Science initiatives.

This is a highly technical, hands-on role focused on designing, building, deploying, operationalizing, and supporting end-to-end machine learning solutions within enterprise cloud environments.

The successful candidate will bring expert-level Python and SQL skills, combined with deep hands-on experience with Azure Machine Learning, Databricks, MLflow, CI/CD, MLOps, model deployment, monitoring, and machine learning lifecycle management.

A critical requirement for this position is proven experience taking machine learning models from prototype / proof of concept through production deployment and ongoing operational support. The successful candidate will build scalable ML pipelines and services and integrate machine learning capabilities into enterprise applications and operational workflows.

This role works closely with Data Scientists, Data Engineers, and other AI and technology stakeholders to accelerate the delivery of enterprise AI solutions from initial proof of concept through production.

Key Responsibilities

Design, develop, deploy, and operationalize end-to-end machine learning solutions in enterprise cloud environments.
Build production-grade ML solutions covering the complete lifecycle, including data preparation, transformation, feature engineering, model development, experimentation, training, validation, deployment, monitoring, maintenance, and production support.
Take machine learning models from prototype / proof of concept through scalable production deployment.
Design and build scalable machine learning pipelines, services, and operational workflows.
Develop and maintain ML solutions using Python and SQL.
Build and operationalize machine learning workloads using Azure Machine Learning (Azure ML).
Develop and support machine learning and data workloads within Databricks.
Implement and manage MLflow for experiment tracking, model management, deployment, and lifecycle management.
Design and implement CI/CD pipelines for machine learning solutions.
Apply MLOps practices to automate model development, testing, deployment, monitoring, versioning, and ongoing lifecycle management.
Implement automated model deployment and release processes across development and production environments.
Establish effective model monitoring and production support processes to ensure reliability and ongoing performance.
Integrate machine learning models and services into enterprise applications, systems, and operational workflows.
Troubleshoot and resolve production issues involving deployed ML models, pipelines, services, and supporting infrastructure.
Collaborate closely with Data Scientists, Data Engineers, and technical stakeholders, while being capable of working independently.
Help establish scalable and repeatable practices that accelerate AI/ML solutions from proof of concept to enterprise production.
Where applicable, contribute to Generative AI, LLM, Agentic AI, and GenAIOps initiatives.

Required Qualifications

Senior-level, hands-on experience as a Machine Learning Engineer, ML Specialist, MLOps Engineer, or similar production-focused ML professional.
Proven experience designing and delivering end-to-end machine learning solutions.
Demonstrated experience taking ML models from prototype / proof of concept through production deployment.
Expert-level Python development skills.
Expert-level SQL skills.
Deep hands-on experience with Azure Machine Learning (Azure ML).
Strong hands-on experience with Databricks.
Strong experience with MLflow, including experiment tracking and model lifecycle management.
Strong experience implementing MLOps practices and frameworks.
Experience designing and implementing CI/CD pipelines for machine learning workloads.
Experience with automated model deployment and release processes.
Strong experience with model deployment, monitoring, lifecycle management, and ongoing production support.
Experience with cloud-native machine learning platforms and services.
Strong understanding of data preparation, transformation, and feature engineering for machine learning.
Experience building scalable ML pipelines and production services.
Experience integrating ML models into enterprise applications and operational workflows.
Demonstrated ability to troubleshoot and support production ML solutions.
Ability to work independently in a highly technical, hands-on delivery environment.
Strong collaboration skills and experience working with Data Scientists, Data Engineers, and other technical teams.

Generative AI / LLM – Nice to Have

Experience with one or more of the following would be considered an asset:

Generative AI (GenAI) solutions and applications.
Large Language Model (LLM) applications.
Agentic AI frameworks and solutions.
GenAIOps practices.
Deployment and operationalization of GenAI / LLM solutions.
Evaluation and testing of GenAI solutions.
Monitoring LLM and GenAI applications in production.
Lifecycle management of enterprise GenAI solutions.
Applying production engineering and operational practices to GenAI, LLM, and Agentic AI workloads.

Ideal Candidate Profile

The ideal candidate is not solely focused on model experimentation or traditional Data Science. We are looking for a hands-on Machine Learning Engineer who combines strong ML knowledge with the engineering, MLOps, cloud, automation, and operational expertise required to put machine learning solutions into production and keep them running successfully.

The successful candidate will be comfortable owning the technical lifecycle from data and feature preparation through model development, deployment, monitoring, lifecycle management, and production support, while collaborating closely with Data Science and Engineering teams.

Success in this role requires a strong combination of Machine Learning Engineering, Azure ML, Databricks, MLflow, Python, SQL, MLOps, CI/CD, software engineering, automation, and production deployment experience, along with the ability to independently help move enterprise AI initiatives from proof of concept into scalable, reliable production solutions.

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More about this job

Responsibilities

Design, develop, and operationalize end-to-end machine learning solutions and scalable pipelines within enterprise cloud environments. Transition ML models from prototype and proof of concept to full production deployment with ongoing operational support.

Requirements

Requires senior-level experience in ML engineering and MLOps with expert-level proficiency in Python, SQL, Azure ML, and Databricks. Candidates must have a proven track record of deploying production-grade ML models and implementing CI/CD pipelines.

Skills

Python
SQL
Azure Machine Learning
Databricks
MLflow
MLOps
CI/CD
Model Deployment
Machine Learning Pipelines
Feature Engineering
Model Monitoring
Production AI Solutions
Generative AI
Large Language Models
Agentic AI
Cloud-native ML Platforms

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning Engineering
MLOps
Azure ML
Databricks
MLflow
Python
SQL
CI/CD
Generative AI
LLM
Agentic AI
GenAIOps
Model Lifecycle Management
Feature Engineering
Production Deployment
Cloud Computing
Data Science
Data Engineering
Scalable Pipelines
Model Monitoring
Enterprise AI
Proof of Concept
Automation
Software Engineering
AI Centre of Excellence

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Jobs in Canada