Becoming a machine learning (ML) engineer in Canada can be one of the most rewarding and exciting careers for you provided you are technologically inclined. This is partly because of Canada’s standing as one of the top innovative tech hubs of the world.
Canada has vibrant tech ecosystems in cities like Toronto, Vancouver, and Montreal and this is why it has attained the position of a leader in global research on artificial intelligence (AI). This has also increased the demand for skilled ML engineers across industries in the country especially those looking to start strong with an entry level machine learning engineer salary Canada offers.
As a machine learning engineer, you can make anywhere between CAD 83,000 and CAD 100,000 a year in Canada, a statistic that shows the importance and standing of these professionals over here.
They perform specialized tasks like developing intelligent systems and algorithms that help machines learn and make predictions. So let us explore how to become a machine learning engineer in Canada.
Source: Glassdoor
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What Is Machine Learning?
Machine learning (ML) is a form of artificial intelligence (AI) that trains algorithms to find patterns in data, learn from experience, and make decisions and predictions without the need for a lot of human programming for each task. This way, the systems also process a lot more information, which helps them get better as a result.
It uses statistical models to identify correlations and create data models that can then perform tasks such as classifying images, detecting fraud, and recommending products. Even as you feed these systems more varied datasets, they become more accurate.
Status in Canada
In Canada, ML is a central pillar of the country’s leadership in the domain of artificial intelligence. The most prominent traits of the industry here are world-class research hubs, rapid industrial adoption, and the Pan-Canadian AI Strategy that brings forth substantial government investment for the sector.
Use in Education
The educational institutions over here, mainly the universities, offer specialized degrees in AI and ML that create skilled professionals who can fill the gaps in this sector in the North American country.
Use in Different Industries
Here, ML is integrated across sectors such as healthcare, finance, agriculture, and natural resources to improve predictive accuracy and automate tasks.
- In the healthcare sector, ML is used for analyzing medical images, diagnosing diseases, and personalizing patient treatments.
- In the financial sector, this technology is used to power fraud detection systems along with algorithmic trading and credit scoring.
- In agriculture, bodies like Statistics Canada use ML along with satellite imagery to predict yield and identify in-season crops.
- In the natural resources sector, oil and gas companies employ ML to predict when sensors might fail and streamline distribution.
Top Roles in the Sector
The top roles in this sector here are machine learning engineer, AI research scientist, data scientist, and natural language processing (NLP) engineer.
Demographic Data
Demographic research indicates that workers with college and bachelor’s degrees, and women, are more likely to work in occupations that expose them to ML than other groups.
ML Standard Setting by Canada
The country is also an active participant in setting standards for the responsible use of such technology. Health Canada has partnered with international agencies to establish Good Machine Learning Practice principles and develop medical devices that ensure effectiveness and safety.
What Is an ML Engineer?
- An ML engineer in Canada is a specialized professional who bridges the gap between software engineering and data science. Their primary role is to design, deploy, and build software that uses AI to run by itself, solve complex business problems, and automate predictive models.
- Their work also centers on designing, maintaining, and deploying scalable AI systems across high-growth sectors like finance, retail, and healthcare.
What Do ML Engineers Do?
In Canada in 2026, ML engineers focus a lot on ML operations (MLOps) and generative AI (GenAI). Their core daily responsibilities are:
- Model Deployment and Development
- Data Pipeline Engineering
- System Orchestration
- Optimization and Monitoring
- Stakeholder Collaboration
Model Deployment and Development: They write high-quality code using programming languages like Python, Java, and C++ to transform prototypes into production-grade systems.
Data Pipeline Engineering: They maintain and build automated pipelines to process and clean large datasets from different sources, such as portable document formats (PDFs), JavaScript Object Notation (JSON), and eXtensible Markup Language (XML), to train models.
System Orchestration: They play the role of orchestrators for AI agent teams by defining roles, collaboration patterns, and rules to align business goals and autonomous workflows.
Optimization and Monitoring: They track model performance continuously, which includes tasks like identifying model drift and retraining systems to make sure that they are accurate over time.
Stakeholder Collaboration: They explain model outcomes to non-technical teams and translate complex business problems to technical AI solutions
How to Become a Machine Learning Engineer in Canada?
ML engineering is one of the most rewarding and fastest-growing careers in Canada these days. This is why everybody wants to know how to become a machine learning engineer in Canada.
1. Building a Strong Educational Foundation
This is the first step in becoming an ML engineer in Canada – a strong academic background. In most cases, employers in Canada look for at least a bachelor’s degree in any of the following subjects:
- Computer Science
- Software Engineering
- AI
- Statistics
- Data Science
- Mathematics
2. Mastering Core Technical and Analytical Skills
As an ML engineer, you will work at the meeting point of programming, data modeling, and statistics. For that, you need to become an expert in the following areas:
- Programming Languages
- Data Management
- Statistics and Mathematics
- Cloud Platforms
- ML Tools and Frameworks
3. Gaining Practical Experience through Projects and Internships
Do you want to know how to become a machine learning engineer in Canada? Then, you should know that recruiters in Canada value practical experience highly. You can make your profile stronger with the following:
- Internships
- Kaggle Challenges
- Co-Op Programs
- Academic Research Projects
Also read: AI and Machine Learning Careers in Canada: Pathways and Job Prospects
4. Earning Professional Certifications
Certifications are proof of your technical knowledge – they also ensure that you stay updated with the evolving standards of the tech industry in Canada. Some of the leading providers of such certifications in Canada are tech giants like:
- Microsoft
- Amazon
- International Business Machines (IBM)
Also read: How Machine Learning Careers Are Evolving with Generative AI in Canada
5. Building Your Network and Advancing Your Career
Networking plays a crucial role in the tech landscape of Canada. To this end, you can attend AI meetups, conferences, and workshops in cities such as Toronto, Vancouver, and Montreal. Doing this will help you connect with recruiters and industry professionals.
Also read: Emerging AI & Machine Learning Trends to Watch in Canada
Roles and Key Responsibilities of a Machine Learning Engineer
Knowing the core roles and responsibilities of an ML engineer is an integral part of knowing how to become an ML engineer:
- Model Research and Development
- Data Management
- Model Optimization and Training
- Monitoring and Deployment
- Collaboration
- Technical Expertise
- Visualization and Analysis
Machine Learning Engineer Salary Outlook
The average annual salary for a machine learning engineer in Canada is CAD 100,000. Entry-level ML engineers with 1 to 3 years of experience earn between CAD 83,000 and CAD 100,000 per year in Canada.
ML engineers in Canada with experience between 4 and 6 years earn between CAD 95,000 and CAD 100,000 a year on average.
Ones with 7 to 9 years of experience earn an average of CAD 97,000 to CAD 100,000 per year.
With 10-14 years’ experience as an ML engineer in Canada you can earn between CAD 100,000 and CAD 200,000 a year on average.
Source: Glassdoor
Also read: Data Science vs. Machine Learning Engineer: Which Career is Right for You?
Essential Skills Required for Machine Learning Engineers
If you want to earn a high salary as an ML engineer, you need the right skills. The table below demonstrates the essential skills for ML engineers in Canada:
| Core Technical Skills | Specialized and Advanced Skills | Soft Skills |
| 1. Programming Languages 2. ML Expertise 3. Deep Learning 4. Data Preprocessing and Handling 5. Statistics and Mathematics 6. Development and Operations (DevOps) 7. ML Operations (MLOps) | 1. Natural Language Processing (NLP) 2. Generative AI 3. Computer Vision 4. Responsible AI 5. Domain Knowledge | 1. Communication 2. Problem-Solving 3. Collaboration 4. Continuous Learning |
Career Path and Growth Opportunities in Machine Learning
Apart from knowing the machine learning scientist job description, you must also have a clear idea of the career paths and growing opportunities available in the domain:
| Entry-Level Machine Learning Engineer Roles | Mid-Level Roles Machine Learning Engineer Roles | Senior Roles Machine Learning Engineer Roles |
| 1. Junior ML Engineer 2. Data Analyst 3. AI Specialist 4. ML Engineering Intern | 1. ML Engineer 2. Data Scientist 3. Applied Scientist | 1. Senior ML Engineer 2. Lead ML Engineer 3. Data Science Manager 4. AI Research Scientist 5. AI Product Manager |
Also Read: In-Demand Machine Learning Jobs in Canada for 2026
Advance Your Machine Learning Career with upGrad
The ML programs offered via upGrad in Canada are among the best bets for becoming an ML engineer in the country. These programs offer you several benefits like flexible online learning, strong career support, and industry-relevant curricula.
- Master of Science in Machine Learning & AI, Liverpool John Moores University
- Executive Diploma in Machine Learning and AI, Indian Institute of Information Technology (IIIT) Bangalore
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FAQs on Entry Level Machine Learning Engineer Salary Canada
If you want to become an ML engineer in Canada from scratch you have to begin by gaining a solid academic foundation in areas like data science and AI.
You need technical and programming skills along with knowledge of statistics and mathematics, and software engineering and soft skills to become an ML engineer in Canada.
The average salary of an ML engineer in Canada ranges between CAD 83,000 and CAD 100,000 a year. This figure increases with experience.
You do not necessarily need a university degree to become an ML engineer in Canada. However, most ML engineers have a bachelor’s degree in a quantitative domain.
For this, you will need to create a strong, project-based portfolio and leverage volunteer opportunities and professional networks.
Entry-level Machine Learning Engineers in Canada typically earn between CAD $80,000 to $110,000 per year, depending on skills, education, and city. Salaries are higher in tech hubs like Toronto and Vancouver, and may include bonuses or stock options.
