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Mlops Machine Learning Engineer Jobs in Toronto, ON

Bree

Machine Learning Engineer

Toronto, ON · On-site

$100 - $130/hr

  • Dental

  • Vision

  • PTO

Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and ... Apply machine learning design patterns to build modular, reusable, and production-ready models.

BDO Canada

Senior Machine Learning Engineer

Toronto, ON

CA$84K - CA$128K/yr

  • PTO

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

  • Medical

  • Dental

  • Vision

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 ...

BDO Canada

Senior Machine Learning Engineer

Oakville, ON · On-site

CA$84K - CA$128K/yr

  • PTO

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 ...

Quincus

Machine Learning Engineer

Toronto, ON

As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.

NTENT

Machine Learning Engineer

Toronto, ON · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Equinix

Principal Machine Learning Engineer

Toronto, ON · Remote

  • Medical

  • Life

  • Retirement

  • PTO

This role blends applied machine learning, software engineering, and MLOps, with a strong focus on building robust, scalable systems rather than purely academic research. Responsibilities * Design ...

New

TheAppLabb

Sr. Machine Learning Engineer

Toronto, ON · On-site

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful ... Solid understanding of MLOps practices: reproducibility, model monitoring, automated retraining.

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 ...

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 ...

Autodesk

Machine Learning Ops Developer

Toronto, ON · On-site

... MLOps Engineer to join our AI/ML Platform team. This role is pivotal in ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps ...

Omers

Lead, AI/Machine Learning Engineer

Toronto, ON · On-site

  • Retirement

The Lead, AI/Machine Learning Engineer will join the AI Delivery and Innovation team within the ... Building and maintaining MLOps/LLMOps/GenAIOps pipelines, including experiment tracking, model and ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... Understanding of FDA regulatory requirements for AI/ML in medical devices Experience with MLOps ...

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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.

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.

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.

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 August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Bree

Toronto, ON • On-site

$100 - $130/hr

Other

Dental, Vision, PTO

Re-posted 14 days ago

Job description

About Bree

Bree is a consumer finance platform building faster, simpler, and more affordable financial services for Canadians who often live paycheck to paycheck. We operate in a massive market that’s historically been underserved by traditional financial institutions, and we’re building products that help customers access short-term credit with a transparent, user-first experience.

To date, 800,000+ Canadians have signed up for Bree—and we believe we’re still early. We’re at an exciting intersection of product-market fit, rapid growth, and a clear path to becoming one of the most important fintech companies in Canada.

We’re at 8-figures of annualized revenue, growing quickly, and profitable. We were part of Y Combinator (Summer 2021) and raised a $2M seed round shortly after.

About the Role

We’re looking for aMachine Learning Engineer to build and scale high-impact, world-class ML systems. You’re passionate about deploying AI solutions, optimizing performance, and driving measurable results. Your work will power critical decisions and shape the future of our technology.

What You'll Do

  • Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference.

  • Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies.

  • Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques.

  • Work with structured and unstructured data, leveraging Pandas, NumPy, and SQL for efficient data manipulation.

  • Apply machine learning design patterns to build modular, reusable, and production-ready models.

  • Collaborate with data engineers to develop high-performance data pipelines for training and inference.

  • Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes.

  • Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.

What You'll Need

  • Proficiency in Python and familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch.

  • Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.

  • Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for tracking experiments and automating workflows.

  • Hands-on experience with data manipulation libraries (Pandas, NumPy) and databases (SQL, NoSQL).

  • Knowledge of cloud-based ML deployment and infrastructure management.

  • Ability to implement real-time and batch inference pipelines efficiently.

  • Strong analytical and problem-solving skills to translate business needs into scalable ML solutions.

  • Eagerness to work in a fast-paced environment and continuously refine ML processes for efficiency and accuracy.

Benefits

  • Top of the market compensation for top performers

  • Comprehensive dental / vision

  • $1,500 annual learning stipend

  • $1,000 annual wellness stipend

  • $250 monthly lunch stipend

  • 2 annual company retreats

  • Parental leave

  • Unlimited PTO

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