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Mlops Machine Learning Engineer Jobs in Toronto, ON

Manulife Financial

Machine Learning Engineer

Toronto, ON · On-site

As a Machine Learning Engineer, you will design, build, and operate the platforms, pipelines, and ... Build reusable patterns for data, ML, and GenAI workloads, following MLOps, LLMOps, and AIOps best ...

New

BDO Canada

Senior Machine Learning Engineer

Toronto, ON

CA$84K - CA$128K/yr

Key Responsibilities MLOps and Platform Development * Design and implement end-to-end MLOps ... Advanced programming skills in Python, with practical experience using popular machine learning ...

Clio

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

Work in an agile environment with our team of machine learning engineers, MLOps engineering and full stack developers across a variety of projects What you may have: * Hands-on experience in model ...

Vancity

Machine Learning Engineer Lead

Toronto, ON · Remote

You will work across the full ML lifecycle, including model development, feature engineering, MLOps, deployment automation, monitoring, and continuous improvement of machine learning systems. Success ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine Learning Engineer Position: Full time Location: Toronto, Ontario (Initially Remote) About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize ...

Tobermory

Machine Learning Engineer

Richmond Hill, ON · On-site

CA$76K - CA$138K/yr

Machine Learning Engineer, NVH develops advanced machine learning systems that help Tesla improve product diagnostics and quality across its vehicles and technologies. Based in Richmond Hill, this ...

Invision AI

Machine Learning Engineer

Toronto, ON · Hybrid

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. Our Company Invision AI is building a ...

Invision AI

Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Machine Learning Engineer to join our Toronto team and help us take our products to the next level in terms of visual intelligence. Our Company Invision AI is building a ...

Clarius Mobile Health

Machine Learning Engineer

Toronto, ON · Remote

CA$110K - CA$130K/yr

Your Role Clarius Mobile Health is seeking a Machine Learning Engineer to contribute to a special project focused on expanding access to ultrasound technology while advancing our next-generation ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

Td

Machine Learning Engineer II

Toronto, ON

CA$154K - CA$199K/yr

Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture, software development practices * Strong coding proficiency: python, R, SQL and / or Scala, cloud ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Toronto, ON

Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

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

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Toronto, ON?

For Mlops Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Toronto, ON look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Toronto, ON are:

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Toronto, ON as of September 2026, with employment types broken down into 86% Full Time, and 14% Temporary. Highlights an 57% In-person, 14% Hybrid, and 29% Remote job distribution.

Machine Learning Engineer

Toronto, ON • On-site

Sequoia Technologies
See more jobs at Sequoia Technologiesexternal

Other

Posted 3 days ago

New

Job description

Location: Remote / Hybrid / On-site
Employment Type: Full-Time

About the Role

We are looking for a skilled Machine Learning Engineer to develop, deploy, and optimize machine learning systems that power innovative AI solutions. You will work closely with data scientists and software engineers to build scalable ML applications for our clients.

Key Responsibilities

Design and develop machine learning pipelines and workflows.

Build, train, and evaluate machine learning models.

Optimize models for performance, scalability, and production environments.

Prepare and process large datasets for model training and validation.

Deploy machine learning solutions into production systems.

Monitor model performance and implement continuous improvements.

Collaborate with cross-functional teams on AI implementation projects.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

Strong knowledge of Python and machine learning frameworks such as TensorFlow or PyTorch.

Experience with data preprocessing, feature engineering, and model evaluation techniques.

Understanding of cloud technologies and containerized deployments.

Excellent problem-solving and debugging skills.

Preferred Skills

Experience with MLOps, Docker, and Kubernetes.

Familiarity with NLP, computer vision, and deep learning techniques.

Knowledge of CI/CD pipelines and model monitoring tools.

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