Demand for ML Engineers in Canada: Hot Cities, Industries, and Tech Stacks
The demand for ML engineers in Canada has truly reached its peak. The reason? Growing attention to implementing AI for business efficiency.
The overall tech workforce growth across the US and Canada slowed last year as employers upskilled their existing teams to leverage AI. This shift in priorities led to a 50% year-over-year increase in AI talent, bringing the total to 517,000 professionals.
However, Canadian companies aren’t just upskilling. They’re also actively hiring ML engineers. In this post, we’ll explore Canada’s hotspot cities, the leading industries, and the must-have tech stacks for ML jobs.
The Current Demand Landscape
Let’s look at where things stand right now for ML engineers in Canada: who’s hiring, why it matters, and how public policy is fueling the trend.
Recent Growth in Canadian ML Hiring
Canada’s tech talent market is seeing a notable uptick in AI-specialty roles. In particular:
- The three markets of Toronto, Vancouver, and Montreal account for 62% of the country’s total AI talent.
- Canada’s overall tech-talent employment grew by 5.9% in 2024, adding around 66,600 jobs — significantly higher than the 1.1% growth in the US in the same period.
- In the Toronto region, between 2018 and 2023, the tech pool grew by 44% (95,900 new jobs), largely driven by demand for AI.
Government Support for AI in Canada
Part of what makes Canada attractive for ML engineers is the policy backing, with the Pan-Canadian Artificial Intelligence Strategy being a key element. Its main pillars include:
Commercialization – led through the National Artificial Intelligence Institutes and Canada’s Global Innovation Clusters, supported by government funding of $60 million and $125 million.
Standards – focuses on enforcing AI frameworks and national standards through the Standards Council of Canada, which received $8.6 million in dedicated funding.
Talent and research – supports the Canadian Institute for Advanced Research in attracting and retaining AI researchers, and strengthens computing infrastructure via the Digital Research Alliance of Canada, funded with $208 million and $40 million.
Global Firms Establishing ML Teams in Canada
Another factor influencing demand is that international and large tech firms are increasingly choosing Canada for expansion and establishment of AI teams. For example, OpenAI is planning to establish data center infrastructure in Canada, building on its massive $500 billion Stargate initiative in the US and similar global projects.
Hot Cities for ML Engineers
Clearly, artificial intelligence and ML engineers in Canada are in high demand. Let’s see where most experts are:
- Toronto. It’s the epicenter of Canada’s AI and ML landscape. Home to Vector Institute, Ada, and Ecopia AI, the city combines research with enterprise adoption. On LinkedIn, there are currently around 45 open ML engineer roles, with employers like Amazon, Autodesk, and Collabera actively hiring.
- Montreal. Montreal leads in AI research and academic collaboration. Anchored by MILA, one of the world’s top AI institutes, the city connects academia and industry better than almost anywhere else. Currently, seven ML engineer positions are listed on LinkedIn, with companies such as Honeywell and Agoda hiring.
- Vancouver. The city supports both startup agility and corporate scale. Such companies as Klue, Variational AI, and Metaspectral fuel the AI community here. LinkedIn shows 13 open ML engineer roles, highlighting the steady demand in entertainment tech, gaming, and applied AI.
- Ottawa/Calgary. These are rising secondary hubs. Together, they show about nine current openings for ML engineers, with such employers as Rackspace Technology and ALS. Ottawa benefits from its government-tech overlap, while Calgary is seeing AI expansion tied to the energy sector.
Industries Driving Demand
While location is certainly a factor in the demand for ML engineers in Canada, the industry vertical is even more critical. Let’s look at the sectors that need skilled AI talent the most:
- Tech & SaaS. No surprise here: the tech sector leads the charge. In fact, professional, scientific, and technical services make up around 30% of AI job postings in Canada. The core focus is on gen AI tools, recommendation engines, and automation platforms.
- Finance & fintech. The finance industry is adopting AI and ML for fraud detection and predictive analytics. Canadian banks and fintech firms, such as RBC, TD, and Wealthsimple, already embed ML models into their products and services.
- Healthcare. According to the SOTI report, the number of organizations using AI for patient care jumped sharply from 72% in 2024 to 87% this year. Adoption is growing, especially in critical areas such as medical imaging and diagnostics.
- Manufacturing & logistics. The Canadian industrial sector, along with the supply chain, benefits from predictive maintenance, robotics, and demand forecasting models. This is also one of the several industries that has shown strong AI demand.
- Government & public sector. Tying back to the national efforts we discussed, the public sector is quickly becoming a critical client for AI talent in Canada. The Pan-Canadian AI Strategy ensures this space is focused on building ethical, transparent, and highly secure systems.
Tech Stacks & Skills Most in Demand
ML engineers in Canada offer specific sets of tools, platforms, and soft skills that help bring efficient models to production. The must-haves include:
- Core languages. Everything starts with fundamental programming skills in Python, R, Java, or C++.
- Frameworks. Building, training, and validating ML models is possible with TensorFlow, PyTorch, Scikit-learn, or MLflow.
- MLOps. Deploying, maintaining, and scaling ML models is done through Docker, Kubernetes, AWS Sagemaker, Azure ML, and GCP AI.
- Data. Building a solid data foundation means being fluent in SQL for querying, Spark for big-data processing, and Airflow for data pipeline creation.
- Soft skills. Non-technical, yet critical must-haves are problem-solving, communication, and collaboration skills.
How Companies Can Attract ML Talent
Given the growing demand for ML engineers in Canada, the competition is also increasing. So, how do you, as a Canadian company, secure a successful hire? Here are several suggestions:
- Competitive pay & remote flexibility. The average salary of an ML engineer in Canada is approximately $121,000 per year, or nearly $60 per hour. Make sure you offer competitive pay. But that’s not all. You should also ensure remote flexibility and performance bonuses to make a big difference in attracting skilled engineers.
- Upskilling programs & research partnerships. The best ML engineers want to keep learning. And the most forward-thinking employers support that. Offer upskilling programs, sponsor conference participation, and provide access to research collaborations with institutes like Vector or MILA.
- Partnering with local development experts. Many firms, especially those new to AI, choose to partner with local development companies like Interio Systems. They understand Canada’s regulatory landscape, data privacy laws, and talent market in all depth.
Integrio’s Role
Integrio Systems helps Canadian companies accelerate their AI and ML initiatives, from developing custom software to scaling teams through staff augmentation. In particular, our AI/ML expertise includes:
- End-to-end AI, ML, and deep learning development
- AI and ML-powered legacy platform modernization
- AI-augmented staffing and team extension services
- AI prompt development
- API integrations with leading AI services
- Managed AI services and project lifecycle support
Why do companies choose us? Here are just a few reasons:
- Access to skilled AI/ML engineers with proven experience
- Dedicated project management for smooth project execution
- Flexible cooperation models and tailored development support
And, most importantly, you get projects that match your unique goals.
Conclusion
The demand for ML engineers in Canada is growing, facilitated mainly by thriving tech hubs, supportive government policies, and industries enthusiastic about AI.
If you’re looking to capitalize on this momentum, partner with a reliable AI development company — like ours. At Integrio Systems, we build, scale, and modernize AI capabilities with the best talent. Interested? Reach out to our teams for more.
FAQ
ML engineers in Canada need a combination of hard and soft skills. On the technical side, these include Python, R, Java, TensorFlow, PyTorch, Docker, Kubernetes, AWS Sagemaker, Azure ML, and SQL/Spark/Airflow. As for soft skills, a good expert is a strong problem-solver and communicator.
The top tech cities in Canada are Toronto, Vancouver, and Montreal, followed by Ottawa and Calgary. These cities either boast a strong startup scene, research hubs, or global tech firms actively hiring ML talent.
The average machine learning engineer salary in Canada is nearly $121,000 annually, according to Talent.com. Entry-level roles typically start around $92,500, while senior roles can reach up to $147,000 per year.
To access the Canadian tech industry and locate ML engineers, companies can use LinkedIn searches, local AI institutes, and job market platforms. Another option is to collaborate with local development companies experienced in AI/ML.
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