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Machine Learning Operations Jobs in Ontario (NOW HIRING)

... machine learning pipelines using Azure and Databricks. The successful candidate will also lead ... Ensure operational reliability, performance, and compliance across all ML workflows. Client and ...

Senior Machine Learning Engineer

Oakville, ON ยท On-site

CA$84K - CA$128K/yr

... machine learning pipelines using Azure and Databricks. The successful candidate will also lead ... Ensure operational reliability, performance, and compliance across all ML workflows. Client and ...

Senior Machine Learning Engineer

London, ON ยท On-site

CA$84K - CA$128K/yr

... machine learning pipelines using Azure and Databricks. The successful candidate will also lead ... Ensure operational reliability, performance, and compliance across all ML workflows. Client and ...

... machine learning pipelines using Azure and Databricks. The successful candidate will also lead ... Ensure operational reliability, performance, and compliance across all ML workflows. Client and ...

... operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan ... As a Senior Machine Learning Engineer, you will work on delivering ML components for innovative ...

New

Join Restaurant Brands International as a Machine Learning Engineer III in Toronto, ON, and drive ... This role combines hands-on model development and operational optimization in a collaborative ...

New

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as ... Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related ...

Senior Machine Learning Engineer

Toronto, ON ยท On-site

CA$170K - 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 ...

Machine Learning Engineer II

Toronto, ON ยท On-site

CA$154K - CA$199K/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 ...

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Showing results 1-20

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.
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.
Machine Learning Engineer (Toronto)

Machine Learning Engineer (Toronto)

Fitch Solutions

Toronto, ON โ€ข On-site

Other

Re-posted 18 days ago


Job description

ย 

The Fitch Group's Emerging Technology team is seeking aย Machine Learning Engineerย to join a team focused on building and supporting Generative AI, Machine Learning (ML), and Data Science solutions across the organization. This position could be based in our Chicago or Toronto offices.ย 

The Emerging Technology team objectives:ย 

  • Implementย AIย &ย ML technologyย in collaborationย with businessย partnersย and product owners ย 

  • Developย and support enterprise-level AI exploration tools and capabilitiesย 

  • Provide guidance and support for safe development and deployment of AIย 

  • Establish andย maintainย policies, guidelines, and processes forย AI/MLย governance,ย includingย third-party AI governanceย 

What We Offer:ย 

  • Aย high impact role with significant visibility,ย workingย on flagship Fitch productsย 

  • An excellent opportunity to work inย cutting-edgeย areasย of machine learning and data scienceย 

  • Anย excellent work culture known for providing a good work-life balanceย 

We'llย Count on You To:ย 

  • Work closely with product squads and partner teams to design, build, integrate, and deploy ML and GenAI solutions in production, while sharing best practices with other engineers.ย 

  • Communicate ML and GenAI concepts clearly to technical and non-technical stakeholders, with a focus on practical application to Fitch use cases.ย 

  • Collaborate with engineers, data scientists, and product partners to develop and deploy ML and GenAI solutions that deliver measurable business value.ย 

  • Partner with data scientists and domain experts toย identifyย practical opportunities where data, ML, and GenAI can improve business outcomes.ย 

  • Build scalable services, pipelines, and workflows for ML and GenAI use cases, with guidance from senior engineers where needed.ย 

  • Support production applications by helpingย maintainย reliability,ย monitoringย performance, and using metrics to improve existing ML solutions.ย 

  • Use cloud services, primarily in AWS, to support data pipelines, model deployment, and LLM-based workflows. Familiarity with Azure services is a plus.ย 

  • Use Python and large-scale workflow orchestration tools (for example, Airflow) to build production-quality services, data pipelines, and integrations across diverse data sources and storage systems.ย 

What You Need to Have:ย 

  • 3+ years of experience as a machine learning engineer or in a closely related software engineering role focused on ML systems.ย 

  • Experience writing production-quality Python code and applying sound software engineering practices.ย 

  • Strong foundationย in machine learning concepts and practical experience applying modern ML techniques to real-world problems.ย 

  • Strong software engineering fundamentals, including code quality, automated testing, version control, observability, and performance optimization.ย 

  • Experience building or integrating Generative AI applications, such as retrieval-augmented generation,ย evaluationย workflows, or agent-assisted systems.ย 

  • Experience building or improving search, retrieval, or data access layers that support ML or GenAI applications.ย 

  • Experience with containerized deployment and orchestration, such as Docker and Kubernetes.ย 

  • Experience with cloud-native ML and data services, especially in AWS. Familiarity with tools such as Bedrock, S3, SageMaker, Azure AI Search, or Azure OpenAI is helpful.ย 

  • Bachelor's degree in computer science, machine learning, data science, applied mathematics, or a related field, or equivalent practical experience.ย 

What Would Make You Stand Out:ย 

  • Passionย for usingย data andย MLย to drive better business outcomes for customersย 

  • Proven ability to work effectively in a distributed team environment and contributeย inย fast-paced settings.ย 

  • Familiarity with credit ratings agencies, regulations, and data productsย 

  • Excellentย written and verbal communication skillsย 

  • Advocateย of good code quality and architectural practicesย 

  • Strong interpersonal skills and ability to work proactivelyย as a team playerย 

Why Fitch?

At Fitch Group, the combined power of our global perspectives is what differentiates us. Our global network of colleagues comes together to accomplish things greater than they ever could alone.

Every team member is essential to our business and each perspective is critical to our success. We embrace a diverse culture that encourages a free exchange of ideas, guaranteeing your voice will be heard and your work will have an impact, regardless of seniority.

We are building incredible things at Fitch and we invite you to join us on our journey.

Fitch Group is a global leader in financial information services with operations in more than 30 countries. Wholly owned by the Hearst Corporation, we are comprised of three main businesses: Fitch Ratings | Fitch Solutions | Fitch Learning.

For more information please visit our websites:ย ย 

www.fitchratings.comย |ย www.fitchsolutions.comย |ย www.fitchlearning.com

Fitch is committed to providing global securities markets with objective, timely, independent and forward-looking credit opinions. To protect Fitch's credibility and reputation, our employees must take every precaution to avoid conflicts of interests or any appearance of a conflict of interest. Should you be successful in the recruitment process at Fitch Ratings you will be asked to declare any securities holdings and other potential conflicts prior to commencing employment. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.

Fitch Group is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.

FOR TORONTOย  ROLES ONLY: Expected base pay rates for the role will be between $100,000 and $130,000 CAD per year. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job-related factors.ย  Base pay is one part of Fitch's total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, long-term incentives, and other benefits sponsored by Fitch.ย