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Machine Learning Engineer Jobs in Ontario (NOW HIRING)

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 fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Infoya

CA$100K - CA$110K/yr

We are seeking a seasoned Machine Learning Engineer - Computer Vision to design, optimise, and deploy deep learning models for large-scale, real-time edge inference. In this role, you will work on ...

Workday

Senior Machine Learning Engineer

Toronto, ON · On-site

Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP. * Programming Mastery: Expert-level proficiency in Python ...

Thri5 Inc.

AI / Machine Learning Engineer

Toronto, ON · On-site

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Ontario

Machine Learning Engineer information

See Ontario salary details

$64.5K

$143K

$218.5K

How much do machine learning engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for machine learning engineer in Ontario is $142,956.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $166,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
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 Machine Learning Engineer jobs in Ontario? For Machine Learning Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Ontario look for? The top searched job categories for Machine Learning Engineer jobs in Ontario are:
What are popular job titles related to Machine Learning Engineer jobs in ON? For Machine Learning Engineer jobs in ON, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Ontario as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 86% Physical, 6% Hybrid, and 8% Remote job distribution, with an average salary of $142,956 per year, or $68.7 per hour.
Machine Learning Engineer 3D Geometry & Multimodal AI Toronto, Canada

Machine Learning Engineer 3D Geometry & Multimodal AI Toronto, Canada

Autodesk

Toronto, ON

CA$123K - CA$180K/yr

Other

Posted 14 days ago

Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

8th of 217 rated software companies

Job description

Job Requisition ID #

26WD99904

Position Overview

We are seeking a Senior Machine Learning Engineer to design, develop, and deploy machine learning solutions for next-generation AI-powered capabilities within Autodesk products. The ideal candidate has expertise across the machine learning lifecycle, including research, experimentation, data pipelines, model training, evaluation, MLOps, and production deployment.

You will work closely with researchers and engineers to develop innovative AI solutions involving 3D geometry, multimodal AI, and generative AI, helping transform research into production-ready product capabilities. You enjoy solving complex technical problems, exploring new ideas, and collaborating across teams to deliver scalable, high-quality machine learning solutions.

Responsibilities

  • Design, develop, and optimize machine learning models for AI-powered product features involving 3D geometry, multimodal AI, and generative AI

  • Build and maintain scalable data pipelines and machine learning workflows for data preparation, model training, evaluation, and inference

  • Work with complex datasets and representations for model training, evaluation, and analysis

  • Design and implement evaluation methodologies, benchmarks, and experiments to measure model performance, robustness, and quality

  • Collaborate with researchers and engineers to transform experimental ideas into scalable, production-ready product capabilities

  • Build and maintain MLOps workflows supporting model versioning, deployment, monitoring, and continuous improvement

  • Analyze model performance, identify failure modes, and implement improvements to enhance model accuracy, reliability, and efficiency

  • Document and present technical designs, experimental results, and findings to collaborators and leadership

Minimum Qualifications

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or equivalent industry experience

  • 5+ years of professional experience developing machine learning solutions

  • Experience working across the machine learning lifecycle, including research, data pipelines, model training, evaluation, MLOps, and production deployment

  • Experience working in research or experimental environments with evolving requirements

  • Proficiency with modern deep learning frameworks (e.g., PyTorch, Hugging Face)

  • Experience with computational geometry and 3D data (e.g., meshes, B-Rep models)

  • Experience working with complex data representations, including 2D and 3D geometry

  • Experience with version control, reproducibility, and deploying machine learning models

  • Hands-on experience using modern AI/GenAI tools to improve software development, experimentation, or machine learning workflows

  • Excellent written and verbal communication skills

Preferred Qualifications

  • Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related field

  • Experience with LLMs or generative AI systems (e.g., fine-tuning, prompting, evaluation, or agentic workflows)

  • Experience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)

  • Experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud Platform)

  • Knowledge of the design, manufacturing, AEC, or media & entertainment industries

  • Experience with Autodesk or similar products (e.g., CAD, CAE, CAM)

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk - it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk's competitive compensation package. For Canada based roles, we expect a starting base salary between $123,000 and $180,400. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

Are you an existing contractor or consultant with Autodesk?

Please search for open jobs and apply internally (not on this external site).

What Autodesk employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982

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