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Senior Machine Learning Engineer Jobs in Toronto, ON

Priceline

Senior Machine Learning Developer

Toronto, ON · Hybrid

CA$155K - CA$180K/yr

Machine Learning Developer The Search Platform at Priceline is the intelligence layer behind how millions of travelers discover and book hotels, flights, rental cars, and packages every day. It ...

United Airlines

Machine Learning Engineer

Toronto, ON · On-site

Five or more years building Deep Learning or Machine Learning models in production environments ... engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data ...

Redhat

Machine Learning Engineer

Toronto, ON · On-site +1

As a Machine Learning Engineer focused on model optimization algorithms, you will work closely with our product and research teams to develop SOTA deep learning software. You will collaborate with ...

Munich Re

Senior ML Engineer

Toronto, ON

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and operationalizing ML solutions-working closely with data scientists, engineers, and business stakeholders to ...

Td

Machine Learning Engineer II

Toronto, ON · 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 ...

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Senior Machine Learning Engineer information

See Toronto, ON salary details

$42.9K

$157.8K

$237.2K

How much do senior machine learning engineer jobs pay per year?

As of Jun 15, 2026, the average yearly pay for senior machine learning engineer in Toronto, ON is $157,772.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,221.00 and $175,598.00 per year, depending on experience, location, and employer.

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 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 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 Toronto, ON? The most popular types of Machine Learning Engineer jobs in Toronto, ON are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Toronto, ON? For Senior Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What cities near Toronto, ON are hiring for Senior Machine Learning Engineer jobs? Cities near Toronto, ON with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you

Machine Learning Engineer (Energy) - MLEEAS

NavitasPartners

Mississauga, ON • On-site

$30/hr

Other

Posted 11 days ago

Job description

Job Title : Machine Learning Engineer (Energy)Industry

Energy & Utilities

Position Overview

The ML Engineer will develop and deploy machine learning models supporting predictive maintenance, energy demand forecasting, asset optimization, and renewable energy production analytics.

Responsibilities
  • Develop machine learning pipelines.
  • Build predictive analytics solutions.
  • Deploy ML models into production.
  • Optimize model performance and monitoring.
  • Collaborate with data scientists and engineers.
  • Support AI-driven operational excellence programs.
Required Skills
  • Python
  • Machine Learning
  • TensorFlow
  • PyTorch
  • Scikit-Learn
  • Databricks ML
  • Feature Engineering
  • Model Deployment
Preferred Skills
  • Predictive Maintenance
  • Demand Forecasting
  • Energy Load Optimization
  • Renewable Energy Analytics
Mandatory Experience
  • 5+ years in Machine Learning Engineering.
  • Must have prior Energy sector experience.

For more details reach at resumes@navitassols.com

Apply