New artificial intelligence careers don't come out of nowhere: they're natural evolutions of existing positions. A backend developer who adds Python and TensorFlow to their toolkit becomes a sought-after candidate. A business analyst who understands the limitations of language models can lead profitable AI projects.
The Montreal market has its unique features. Bilingualism remains an asset, and Law 25 on data protection creates new needs.
Key takeaways
- AI positions are evolutions of existing tech roles, not entirely new creations.
- The Montreal market prioritizes practical application over pure research.
- Salaries range from $75K to $160K depending on experience and specialization.
- Compliance (Law 25) creates strong demand for hybrid legal-tech profiles.
Your current skills in development or analysis provide a solid foundation for pivoting to AI.
The 4 most sought-after technical profiles in Quebec
What we observe in our recruitment mandates is clear: Montreal companies are primarily looking for professionals who can deliver functional solutions. Not theorists. These careers aren't futuristic, they're modernized versions of positions you already know.
Machine Learning Engineer (ML Engineer)
The ML Engineer puts models into production. It's simple: a model that stays in a Jupyter notebook serves no one. This profile takes the work of data scientists and transforms it into applications that function at scale.
Quick job profile
- 🎓 Ideal Background: Bachelor's in Computer Science or Software Engineering
- 💻 Key Tech: Python, TensorFlow/PyTorch, Docker, Kubernetes
- 🔥 Demand: Very high
What we're seeing: companies readily accept solid backend developers who demonstrate curiosity for ML. A candidate with 3 years in Java Spring Boot and 6 months of personal Python/ML projects often beats out a fresh graduate with an AI master's but no production experience.
Data Architect
Without clean and accessible data, AI remains a concept. The data architect builds the infrastructure that powers models. They design pipelines, ensure data quality, and make sure AI teams can quickly access what they need.
Quick job profile
- 🎓 Ideal Background: Experience in databases and system integration
- 💻 Key Tech: SQL, Spark, Airflow, dbt, Cloud (AWS/Azure/GCP)
- 🔥 Demand: High (particularly in manufacturing SMEs)
This profile bridges traditional IT and new artificial intelligence careers. Montreal companies launching into AI quickly realize their problem isn't a lack of algorithms but data scattered across 15 different systems.
MLOps Specialist
MLOps applies DevOps principles to the AI model lifecycle. They automate deployment, monitor model performance in production, and manage versioning. This career is experiencing rapid growth in Montreal, particularly in downtown fintechs and insurtechs.
Quick job profile
- 🎓 Ideal Background: DevOps or software engineer with an appetite for ML
- 💻 Key Tech: CI/CD, MLflow, Kubeflow, monitoring
- 🔥 Demand: Strongly growing
Contrary to popular belief, you don't need a PhD to excel in MLOps. What our clients are looking for: someone who understands continuous deployment challenges and knows that a model can degrade over time.
Prompt Engineer
Let's be direct: "Prompt Engineer" as a standalone position remains rare in Quebec. What we're seeing instead are developers or business analysts being asked to master prompt engineering as an additional skill.
A few Montreal companies are recruiting dedicated specialists, mainly in marketing agencies or startups building products around LLMs. But for many cases, this skill is added to an existing role.
💡 Our advice
If you see a "Prompt Engineer" posting at $120K, verify the real expectations. Often, the position also requires Python development, API integration, and project management.
Emerging careers: governance and product
Artificial intelligence is moving out of laboratories and into business departments. This transition creates new roles that combine technical understanding with strategic vision. These profiles are particularly sought after in Quebec SMEs that want to integrate AI without diving in blindly.
AI Product Owner/Manager
The AI Product Owner bridges technical teams and business needs. They define the product vision, prioritize features, and ensure the developed AI solves real customer problems.
Quick job profile
- 🎓 Ideal Background: Product Management + technical basics
- 💻 Key Tech: Understanding of AI capabilities and limitations
- 🔥 Demand: Growing (especially in scale-ups)
Ethics and compliance officer (Law 25)
Here's a career born directly from Quebec regulation. Law 25 on the protection of personal information imposes strict obligations on companies using AI to process data from Quebec citizens. Fines can reach $10 to $25 million.
Quick job profile
- 🎓 Ideal Background: Law + technical understanding, or vice versa
- 💻 Key Tech: Governance frameworks, algorithm auditing
- 🔥 Demand: Growing
New artificial intelligence careers now include profiles that audit automated systems to ensure they don't discriminate and respect user consent.
AI salary grid in Montreal (2025)
Here are the real ranges we observe in the Montreal market, in Canadian dollars.
| Career | Junior (0-2 years) | Intermediate (3-5 years) | Senior (5+ years) |
| ML Engineer | $75K - $95K | $100K - $130K | $130K - $160K |
| Data Architect | $80K - $100K | $110K - $140K | $140K - $170K |
| MLOps Specialist | $70K - $90K | $95K - $120K | $120K - $150K |
| AI Product Owner | $85K - $105K | $110K - $135K | $135K - $160K |
| AI Compliance Officer | $75K - $95K | $100K - $125K | $125K - $150K |
These ranges reflect the reality of the Quebec market. In Toronto, add 15-20%. In Vancouver, 10-15%. But in Montreal, the more affordable cost of living partially offsets this gap.
An important point: Montreal companies often offer attractive packages including flexible remote work, comprehensive insurance, and group RRSPs. When evaluating an offer, look at the complete package.
How to train and pivot to AI?
The good news for current developers and analysts: you don't have to start from scratch. New artificial intelligence careers build on foundations you already have. Here's how to strategically fill the gaps.
Technical skills (hard skills)
Your goal isn't to master everything but to build a coherent profile that meets Montreal market needs.
The essentials:
- Python: The dominant language in AI. If you're coming from Java or C#, invest 2-3 months to get comfortable.
- PyTorch or TensorFlow: Pick one to start with.
- Advanced SQL: Data lives in databases. Master joins, CTEs, and query optimization.
- Cloud: AWS dominates in Montreal, followed by Azure. GCP is less in demand. Focus on data-related services (S3, RDS, SageMaker).
Differentiating skills:
- Git/GitHub: Mandatory. AI teams work collaboratively.
- Docker: To containerize your models and facilitate deployment.
- REST APIs: To expose your models to other applications.
💡 What we recommend to our candidates
Build 2-3 concrete projects you can show. A GitHub portfolio with applied projects is better than a certificate without practice.
Certifications valued by recruiters
Certifications don't replace experience, but they signal your seriousness and fill gaps on your resume.
Local Training (Quebec):
- Mila: Highly respected continuing education programs
- IVADO: Practical workshops and recognized certifications
- Polytechnique Montreal: Microprograms in AI and data science
- ÉTS: Short programs in machine learning
International Certifications:
- Google Cloud Professional ML Engineer: Recognized and practical
- AWS Certified Machine Learning - Specialty: Useful given AWS dominance
- Microsoft Azure AI Engineer: Relevant for companies using Azure
- DeepLearning.AI (Coursera): Andrew Ng's course remains a reference.
Recruiters value a local certification (Mila, IVADO) accompanied by concrete projects more than a collection of Coursera badges without practical application.
How long does it take? Expect 6 to 12 months of training and practice for a credible transition if you already have a solid technical foundation. Less if you're targeting hybrid roles like AI product owner.
Why work with a specialized placement agency?
The market for new artificial intelligence careers in Montreal is opaque. The best positions aren't posted on LinkedIn or Indeed. Here's why working with an IT placement agency makes a difference.
Access to the hidden market
Some opportunities we feature are never published publicly. Why? Companies want to avoid being overwhelmed with unqualified applications. They prefer working with headhunters who pre-select profiles.
Advice on your market value
Many candidates underestimate or overestimate their value. At Fed IT, we know the real salary grids of Montreal companies. We position you at the right level.
Time and energy savings
Applying to dozens of online postings is exhausting and often unproductive. We do the sorting upfront. We only present opportunities that truly match your profile and salary expectations.
For HR directors and CTOs: we prevent costly recruitment mistakes. We validate technical skills before presenting candidates to you.
Ready to seize the opportunities?
New artificial intelligence careers are no longer a future trend. They're here now, in Montreal. Companies are hiring. Salaries are competitive. And your current skills already give you a head start.
Are you a candidate?
Do you have skills in development, data, or project management? Don't miss your chance. Send us your resume to access unpublished opportunities and discuss your career evolution toward AI.
Are you a recruiter or executive?
Looking to recruit these rare profiles for your team in Montreal or elsewhere in Quebec? Let's discuss your AI recruitment needs and how we can help you build your team.
