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Senior Machine Learning Engineer Jobs in Ontario

Machine Learning Engineer

Toronto, ON ยท On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning Engineer

Toronto, ON ยท On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

Machine Learning engineer

Toronto, ON ยท On-site

CA$67K - CA$124K/yr

Computational Thinking and Programming. * Deep Learning. * Machine Learning. * Scaling Models. * Continuous Integration and Continuous Delivery/Deployment. * ML algorithm. * Verbal & written ...

We're in search of an exceptional ML engineer with extensive experience in suggesting, exploring ... Experience fine-tuning LLMs for specific learning tasks Experience deploying full-stack features to ...

What you'll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to ...

Machine Learning Engineer II

Toronto, ON ยท On-site

CA$154K - CA$199K/yr

Day-to-day as a Machine Learning Engineer: * Join a world-class team of AI developers with an extensive track record. * Architect scalable machine learning and Gen AI systems that integrate with ...

Machine Learning Engineer - Enterprise

Toronto, ON ยท On-site

CA$150K - CA$400K/yr

We are seeking a skilled, detail-oriented, and passionate Machine Learning Engineer to join our enterprise team. In this pivotal role, you will be at the forefront of developing and deploying ...

Showing results 41-60

Senior Machine Learning Engineer information

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Ontario?

The most popular types of Machine Learning Engineer jobs in Ontario are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Ontario?

For Senior Machine Learning Engineer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in Ontario look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Ontario are:

What cities in Ontario are hiring for Senior Machine Learning Engineer jobs?

Cities in Ontario with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Ontario as of August 2026, with employment types broken down into 93% Full Time, and 7% Contract. Highlights an 74% In-person, 13% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer

Toronto, ON โ€ข On-site

CA$67K - CA$124K/yr

Full-time

Medical, Life, Retirement

Posted 8 days ago


Job description

Application Deadline:

08/27/2026

Address:

33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

Hybrid Work Model

Researches, builds, and implements scalable artificial intelligence systems capable of learning and making predictions to business requirements. Enhances data pipelines and lakes to ensure data is clean, accurate, and optimized for machine learning models. Monitors, evaluates, and optimizes learning processes to continuously improve high-performance models. Works with other data and analytics professionals to optimize, refine, automate and scale analysis into repeatable analytics solutions and decision support tools.

  • Designs and develops machine learning (ML) and deep learning systems.
  • Runs machine learning tests and experiments. Trains and retrain systems to prevent drift and optimize results.
  • Solves complex problems with multi-layered data sets, extends existing ML frameworks and optimizes existing machine learning libraries.
  • Develops Machine Learning apps, implements algorithms, and builds tools to apply ML frameworks.
  • Turns unstructured data into useful information by auto-tagging images and text-to-speech conversions.
  • Develops ML algorithms to analyze huge volumes of historical data to make predictions.
  • Runs tests, performs statistical analysis, and interprets test results.
  • Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
  • Exercises judgment to identify, diagnose, and solve problems within given rules.
  • Works independently on a range of complex tasks, which may include unique situations.
  • Broader work or accountabilities may be assigned as needed.
  • Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.

Qualifications:

Foundational level of proficiency:

  • Systems Thinking.
  • Mathematics, Statistics & Operations Research.
  • Critical thinking.
  • Creative reasoning.

Intermediate level of proficiency:

  • Computational Thinking and Programming.
  • Deep Learning.
  • Machine Learning.
  • Scaling Models.
  • Continuous Integration and Continuous Delivery/Deployment.
  • ML algorithm.
  • Verbal & written communication skills.
  • Collaboration & team skills.
  • Analytical and problem solving skills.
  • Data driven decision making.
  • Typically between 4 - 6 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
  • Technical proficiency gained through education and/or business experience.

Salary:

$67,200.00 - $124,200.00

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.