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Machine Learning Operations Jobs in Ontario (NOW HIRING)

fgf brands

Summary We are looking for a versatile and hands-on individual who thrives on working with hardware, machine learning operations (MLOps), and supporting a dynamic data science team. The ideal ...

Manulife

Machine Learning Engineer

Toronto, ON · On-site

We are seeking an innovative and experienced Machine Learning Engineer to join our AI + Data team, a cross-functional group spanning Operations, Technology, and Marketing. Our team's mission is to ...

Bmo

Machine Learning Engineer

Toronto, ON · On-site

CA$82K - CA$154K/yr

Runs machine learning tests and experiments. Trains and retrain systems to prevent drift and ... Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. * Verbal ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability * Write clean ...

Clio

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

Summary: We are currently seeking a Machine Learning Engineer to join our rapidly growing ... Collaborate cross-functionally with engineering, product management, operations and data science to ...

Autodesk

Machine Learning Ops Developer

Toronto, ON · On-site

Drive the operational excellence of our AI/ML Platform by implementing and optimizing MLOps ... Design and implement automated deployment pipelines for machine learning models, ensuring seamless ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

BMO Capital Markets

Machine Learning Engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

BMO Capital Markets

Machine Learning engineer

Toronto, ON · On-site

CA$67K - CA$124K/yr

Mathematics, Statistics & Operations Research. * Critical thinking. * Creative reasoning. Intermediate level of proficiency: * Computational Thinking and Programming. * Deep Learning. * Machine ...

Socket.dev

$110 - $170/hr

The Product Operations machine learning team is seeking a machine learning research engineer to conduct research in anomaly detection and automated machine learning to address domain-specific ...

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Machine Learning Operations information

What is the difference between Machine Learning Operations vs Data Scientist?

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks among well-paying tech jobs.

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.

Machine Learning Operations Engineer

fgf brands

On-site

Full-time

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

MLOps & Production Support Specialist

We’re a naan traditional company…

 

Summary

We are looking for a versatile and hands-on individual who thrives on working with hardware, machine learning operations (MLOps), and supporting a dynamic data science team. The ideal candidate will have a broad technical skill set and the ability to tackle various challenges, including hardware setup, system optimization, and machine learning workflows.

 

What FGF Offers:

  • FGF believes in Home Grown Talent, accelerated career growth with leadership training.  Unleashing Your Potential 
  • Competitive Compensation, Health Benefits, & a generous flexible medical / Health spending account
  • RRSP matching program
  • Tuition reimbursement
  • Discount program that covers almost everything under the sun - Restaurants, gyms, shopping etc. 

Primary Responsibilities

  • Deploy machine learning models on hardware platforms with a focus on edge AI and IoT systems.
  • Set up servers and deploy models to support production ML workloads.
  • Leverage containerization (e.g., Docker) for scalable, repeatable deployments.
  • Support and maintain servers and vision models running in production, ensuring uptime, performance, and reliability.
  • Troubleshoot and resolve support tickets related to production model issues, providing timely fixes and root-cause analysis.
  • Automate workflows to streamline machine learning pipelines and maximize reproducibility.

 Required Experience

Technical Expertise

  • Deep familiarity with Linux environment, machine learning workflows and MLOps best practices.
  • Knowledge of platforms like NVIDIA Boards, Raspberry Pi, or comparable devices.
  • Proficiency in setting up hardware systems, including advanced troubleshooting.
  • Experience with containerization (Docker) and cloud services integration.
  • Experience with server setup, configuration, and ongoing maintenance in production environments.
  • Experience deploying and supporting vision models in production, including monitoring and troubleshooting live inference systems.
  • Comfortable managing and resolving support tickets tied to production model issues.

Programming Skills

  • Proficiency in Python; familiarity with ML frameworks like PyTorch, Tensorflow is a plus.
  • Experience with hardware acceleration tools such as NVIDIA TensorRT is advantageous.

Problem Solving & Collaboration

  • A relentless drive to find elegant, scalable solutions to complex problems.
  • Strong communication skills and a commitment to teamwork.

What is the recipe for a great career at FGF?

Working at FGF Brands, there is never a dull moment! As a successful company that is continually growing there is always challenging yet rewarding work to be a part of. We have an entrepreneurial spirit which encourages all our team members to use their own creativity and out of the box thinking to come up with solutions and new ideas.

Disclaimer: The above describes the general responsibilities, required knowledge and skills.  Please keep in mind that other duties may be added or this description may be amended at any time.

 

In compliance with Ontario’s Bill 190, we confirm that this posting represents a current, existing vacancy within our organization

FGF Brands may use Artificial Intelligence (AI) tools as part of our recruitment and selection process. These tools may assist in screening, assessing, or selecting applicants. AI tools are used to support our recruitment process, with final hiring decisions made by our recruitment and hiring teams.

FGF Brands is committed to providing an accessible recruitment process. Accommodations are available upon request for candidates taking part in all aspects of the recruitment and selection process. If you require an accommodation, please let our recruitment team know, and we will work with you to meet your accessibility needs.

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