Design and develop AI solutions, mentor team members, and advise clients on AI technologies while ensuring software quality and performance.
Who we are
We’re a thriving and agile tech development firm. People are at the center of everything we do. Simply put, we care. Our team personally cares about our clients and the world around them, and we care about our team’s life-long dreams, aspirations, and career development.
We strongly believe in the power of community. This is why we seek opportunities to build meaningful relationships with everyone around us.
We celebrate diversity in all its forms. Backgrounds, personalities, career paths, languages... you name it. We actively innovate, learn, and share stories around the topic. We want everyone to feel welcomed and included in all we do.
We like having fun and enjoying ourselves. We wake up every day inspired to build a more efficient and enjoyable world.
Role overview
As an Applied AI Scientist, you design, build, and ship AI solutions that solve real client problems. You combine strong software engineering habits with hands-on AI/ML expertise, and you’re comfortable moving from exploration to production. You collaborate closely with technical and non-technical teammates, mentor others, and help teams make sound technical decisions as we deliver enterprise-grade AI software.
The technologies below are a reference point for our stack. Above all, we hire for strong fundamentals, judgment, and growth potential.
Your key responsibilities
- Build and deploy AI solutions that deliver measurable business impact
- Identify high-value opportunities to apply AI technologies and tooling
- Develop software aligned with specifications and documentation (SRS, C4)
- Define, document, and communicate non-functional requirements (performance, reliability, security, maintainability)
- Turn experiments into production-ready components (evaluation, monitoring, iteration)
- Coach colleagues on applied AI best practices and implementation approaches
- Take initiative, own deliverables end-to-end, and manage priorities effectively
- Uphold and strengthen software development guidelines and quality standards
- Research, test, and implement new techniques, models, and tools
- Advise clients on technical direction, trade-offs, and solution design
The ideal candidate
- 5+ years of software engineering experience, including 3+ recent years working hands-on with AI/ML (Deep Learning, Computer Vision, NLP, Generative AI, Predictive Analytics, etc.)
- Master’s or PhD in Computer Science / Software Engineering specialized in AI, or equivalent experience
- Intermediate or conversational French (minimum)
You should be proficient with
- Python 3
- Core Python libraries (NumPy, Pandas, PyTorch, Scikit-learn)
- Data analysis, cleaning, processing, and augmentation
- Deep learning frameworks (TensorFlow, Keras, PyTorch)
- AI services on at least one major cloud platform (AWS, Azure, Google Cloud, etc.)
- MLOps (training, deployment, monitoring, reproducibility, CI/CD for ML)
- Testing practices (unit, functional, E2E, etc.)
- Modern development methodologies (Agile, Scrum, XP, Kanban, Shape Up, etc.)
It’s a plus if you have experience with
- Go, Java, and/or JavaScript
- Enterprise software development
- In-memory object storage, caching, and queue systems
- Microservices and serverless architectures
- Domain-driven design
- A modern client-side framework/library (Angular, React, Svelte, etc.)
What we offer
- Competitive Salary and contribution to your pension plan (RRSP)
- Flexible hours of work and choose how you work
- Work from anywhere up to 8 weeks
- Paid sabbatical
- Wellness and productivity spending account
- Parental program
- Activities
- Training
- And more...
The process for this role if you are selected
1. 20 min - Initial introductory call with a person from our technical team.
2. 90 min - In-person interview at our office
3. Offer presentation
Only considered candidates will be contacted. Read our full hiring process here.
Top Skills
AWS
Azure
GCP
Keras
Numpy
Pandas
Python 3
PyTorch
Scikit-Learn
TensorFlow
Osedea Montréal, Québec, CAN Office
4000 St-Ambroise, 270, , Montréal, PQ , Canada, H4C 2C7
Similar Jobs
Fintech • Insurance • Financial Services
The Senior Applied Machine Learning Scientist will lead validation efforts for AI/ML models, particularly Generative AI and Deep Learning. Responsibilities include team leadership, model evaluation, development of validation standards, and communication with regulators. The role requires extensive knowledge in machine learning methodologies and technologies, as well as project management skills.
Top Skills:
AIAWSAzureDeep LearningGenerative AiHadoopHuggingfaceLangchainMachine LearningNlpPromptflowPysparkPythonPyTorch
Fintech • Insurance • Financial Services
This role leads a team of AI/ML professionals, focusing on predictive AI systems. Responsibilities include mentoring, strategic planning, and collaboration with cross-functional teams to deliver enterprise-level solutions.
Top Skills:
AIData SystemsMachine LearningMl
Fintech • Insurance • Financial Services
Lead a team of machine learning scientists, develop AI systems for complex business problems, and drive innovation in AI methodologies. Ensure compliance and foster a collaborative work environment.
Top Skills:
AIData AnalyticsMachine LearningMachine Learning FrameworksPythonR
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
