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Machine Learning Operations Jobs in Ontario (NOW HIRING)

Magna

Machine Learning Engineer

Milton, ON · On-site

The Machine Learning Engineer will play a pivotal role in driving innovation and operational efficiency through data-driven solutions leveraging machine learning and artificial intelligence. You will ...

United States Digital Space LLC

Job Responsibilities The Machine Learning Engineer will play a pivotal role in driving innovation and operational efficiency through data‑driven solutions leveraging machine learning and artificial ...

New

Themis

Machine Learning Engineer

Mississauga, ON · On-site

CA$85K - CA$135K/yr

Machine Learning Engineer About Themis Intelligence Themis Intelligence builds the Utility ... Our systems transform complex operational data into clear, high-confidence decisions. We design ...

TD

Machine Learning Engineer

Toronto, ON · On-site

CA$120K - CA$250K/yr

... focusing on automation, operation efficiency, and reliabilityWrite clean, efficient, and ... machine learning and deep learningStrong coding proficiency in Python, Java, C, or C++You value ...

Td

Machine Learning Engineer

Toronto, ON · On-site

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$152K - 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 ...

Themis Solutions Inc.

Machine Learning Engineer

Toronto, ON · On-site

CA$129K - CA$174K/yr

We are seeking a Machine Learning Engineer to join our growing engineering team. This role is open ... Collaborate cross‑functionally with engineering, product, operations, and data science to ...

New

Socotra, Inc.

Machine Learning Engineer

Toronto, ON · On-site

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the ... operational overhead * Design and implement feature pipelines, model training workflows, and ...

New

Lyft

Machine Learning Engineer

Toronto, ON · On-site

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the ... operational overhead * Design and implement feature pipelines, model training workflows, and ...

New

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Showing results 1-20

All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in Ontario

Machine Learning Operations information

Is ML a high paying job?

Machine Learning Operations (MLOps) roles are generally well-paid due to the specialized skills required, such as expertise in cloud platforms, programming, and data management. Salaries tend to be higher than average tech roles and can increase with experience, certifications, and knowledge of tools like TensorFlow or Kubernetes.

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.

What engineer makes $500,000 a year?

Senior machine learning operations engineers with extensive experience, advanced skills in automation, cloud platforms, and deployment pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such roles often require expertise in tools like Kubernetes, Docker, and cloud services, along with strong problem-solving and leadership abilities.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, often found in large tech companies or innovative startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and overseeing complex models. AI may automate some routine aspects, but MLEs' expertise in data engineering, model optimization, and deployment remains critical for effective AI solutions.
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Ontario as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Manager, Machine Learning Operations (MLOps)

Manager, Machine Learning Operations (MLOps)

Wawanesa Insurance

Toronto, ON • Hybrid

CA$140K - CA$180K/yr

Other

Retirement, PTO

Posted 18 days ago

Job description

Job ID: 9789 


Employment Type: Existing Role 
Working Business Language: English 
 

Salary: At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus plan, leave of absence top-up programs and provided with generous vacation time, personal days, premium free benefits and pension plan. 
 

The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $140,000 - $180,000.  Candidates with salary expectations outside of the range are still encouraged to apply.

About Us
At Wawanesa, we offer a hybrid work environment that offers flexibility to our employees in balancing in-office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work. You may work from any of the following locations: Winnipeg, MB; Calgary, AB; Toronto (North York), ON.
 

The Wawanesa Mutual Insurance Company ("Wawanesa Mutual"), founded in 1896, is one of Canada's largest mutual insurers, with over $3.5 billion in annual revenue and assets of $10 billion (CAD). Wawanesa Mutual, with its National Headquarters in Winnipeg, is the parent company of Wawanesa Life, which provides life insurance products and services throughout Canada, and Western Financial Group, which distributes personal and business insurance across Canada. Wawanesa proudly serves more than 1.7 million members in Canada, and we are home to more than 3,300 employees distributed across the Canadian regions and communities where we operate. We give back to organizations that strengthen communities, donating more than $3.5 million annually to charitable organizations, including over $2 million annually in support of people on the front lines of climate change. We are also proud to be recognized as one of Manitoba's Top Employers. To learn more visit wawanesa.com. 


We are currently looking for dedicated, driven, and enthusiastic individuals who thrive in an environment that welcomes change and are looking for an opportunity for diverse experience and advancement on a growing team.
 

Job Overview

The Manager, Machine Learning Operations (MLOps) contributes to Wawanesa's success by bringing your passion for predictive modeling and machine learning. In this role, you will lead the Machine Learning Operations (MLOps) function, ensuring scalable, reliable, and cost-effective deployment of machine learning solutions across the enterprise. The manager is leading a team responsible for taking machine learning applications to support decision making across the organization from concept to production, with accountability for platform architecture, production reliability, governance, and lifecycle management.   

Job Responsibilties

  • Work directly with organizational leaders to introduce advanced analytics to all functions within the organization, and to foster the advancement and adoption of analytic assets.
  • Develop and advance analytic standards and processes that enable all aspects of advanced analytics including applied research, proof of concept, deployment of production grade ethical machine learning models, model monitoring and measurement.
  • Own and evolve the enterprise MLOps platform strategy, including CI/CD for ML, model registry, feature management, orchestration, monitoring, and observability frameworks.
  • Establish standardized deployment patterns and infrastructure-as-code practices to reduce bespoke solutions and increase reuse across teams.
  • Model lifecycle governance from development through validation, deployment, monitoring, retraining, and retirement.
  • Identify and organize educational initiatives aimed at the development of overall inter- and intra-departmental knowledge.
  • Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.
  • Perform other duties as assigned.
Qualifications
  • A minimum of five years of experience in developing and deploying enterprise-scale machine learning solutions, and one year of people leadership with proven ability to build high performing teams.
  • Strong business acumen with advanced analytical and problem-solving skills, with the ability to recognize, and identify critical issues.
  • Excellent interpersonal, presentation and communication skills, with the ability to effectively convey complex ideas in a simple, persuasive, and eloquent manner.
  • Comfortable confronting difficult issues and diplomatic in delivery of challenging messages.
  • Ability to establish and maintain good relationships with key stakeholders.
  • Advanced planning and organizing skills, with the ability to manage and prioritize a busy workload and multiple projects.
  • Knowledge and experience in the insurance industry is considered an asset.

#Li-Hybrid #LI-JB3


Diversity Equity, Inclusion& Belonging
At Wawanesa, we are committed to Diversity, Equity, Inclusion and Belonging (DEIB) and believe that our strength lies in the diversity of our people - this is supported by having a representative workforce.

We welcome applications from all qualified candidates, including racialized persons, women, Indigenous Peoples, persons with disabilities, members of the 2SLGBTQIA+ community, gender-diverse and neurodiverse individuals, and anyone who can contribute to the further diversification of thought and ideas. 
 

We aim to ensure our recruitment process is accessible to all candidates. If you require accommodations during any stage of the recruitment process, please reach out in confidence to jobs@wawanesa.com.
 

All Wawanesa job applicants are subject to Wawanesa's Privacy Policy.

Please note that the recruitment process for this position may involve the use of AI tools to screen, assess, or select applicants. All final decisions are taken or reviewed by human recruiters and human hiring leaders in compliance with all applicable legislation.  
 

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