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Scientific Machine Learning Jobs in Quebec (NOW HIRING)

LawZero

Machine Learning Manager

Montreal, QC

We are seeking a Machine Learning (ML) Manager to join our growing team dedicated to a novel AI ... You will bridge the gap between cutting-edge scientific theory and large-scale engineering ...

SAP

Senior AI Machine Learning Engineer

Montreal, QC · On-site

About the Role We are hiring a Senior Machine Learning Engineer Scientist to lead the development of scalable graph-based and transformer-based modeling systems, along with production-grade ML ...

Capco

Machine Learning Engineer

Montreal, QC

Plus de 5 ans d'experience dans des roles en apprentissage automatique ou en science des donnees ... This role focuses on the full lifecycle of machine learning models-from development and ...

Intact Financial

Senior Data Scientist

Montreal, QC

About the role Intact is looking for a Data Scientist to turn complex data into practical solutions ... Use machine learning and advanced statistical methods to identify trends and patterns in complex ...

TELUS

L4 Technical Professional

Montreal, QC · On-site

You will work closely with a team of data scientists and data engineers to deploy solutions and drive innovation using machine learning and NLP techniques. The ideal candidate has a deep ...

Intact Financial

Data Scientist II

Quebec, QC · On-site

About the role Intact is looking for a Data Scientist to turn complex data into practical solutions ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

Intact Financial

Data Scientist II

Montreal, QC · On-site

About the role Intact is looking for a Data Scientist to turn complex data into practical solutions ... Utilize machine learning and advanced statistical methods to identify trends and patterns in ...

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Quebec? For Scientific Machine Learning jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Quebec look for? The top searched job categories for Scientific Machine Learning jobs in Quebec are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Quebec as of June 2026, with employment types broken down into 3% As Needed, 81% Full Time, 13% Part Time, and 3% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution.

Machine Learning Manager

LawZero

Montreal, QC

Other

Medical, Retirement, PTO

Posted 21 days ago

Job description

We are seeking a Machine Learning (ML) Manager to join our growing team dedicated to a novel AI safety agenda. In this role, you will join the group tasked with designing and implementing innovative ML models using the Scientist AI approach developed by Yoshua Bengio. 

As both a people manager and technical leader, you will guide research team members and spearhead complex projects within a matrix structure. You will bridge the gap between cutting-edge scientific theory and large-scale engineering execution. 

People management

  • Lead, mentor and inspire a team of mission-minded and highly skilled ML research scientists and engineers. 
  • Partner with other leaders and talent acquisition to scale the organization. Drive technical hiring, active sourcing, interviewing, and onboarding to accelerate our research velocity.
  • Coach technical team members to help them do their best work and develop new skills, while ensuring a high quality, supportive employee experience.
  • Lead with humility to cultivate an inclusive, collaborative and intellectually rigorous environment.
  • Display managerial courage as needed to continue fostering a healthy and productive work environment as we scale. 

Technical leadership

  • Guide cross-functional project teams tackling complex, sometimes unchartered, scientific and engineering challenges within an evolving matrix structure.
  • Manage and optimize research workflows to ensure rigorous, reproducible results at the frontier model scale.
  • Advocate for our research agenda internally and externally, maintaining momentum to achieve breakthroughs and overcome complex technical roadblocks.
  • Collaborate within and across projects, bridging theoretical concepts and advanced engineering. 

Required skills and qualifications

Background & experience

  • PhD in a relevant field (e.g., Computer Science, Mathematics).
  • 10+ years experience in machine learning / deep learning
  • 5+ years experience leading projects and people 
  • Experience leading machine learning / deep learning research projects
  • Experience in foundation models 

Role fit

  • Strong alignment with LawZero's existing research agenda.
    • Note: We highly recommend that interested candidates read into the Scientist AI framework before confirming interest. 
  • Advanced oral and written communication skills, with the ability to translate complex scientific concepts for diverse audiences. 
  • Resilience and advanced problem-solving skills when facing ambiguous or unmapped technical challenges.
  • Proven ability to push the boundaries of our research while fostering a sustainable, healthy work environment for your team. 

What we offer

  • The chance to contribute meaningfully to a globally critical initiative
  • Comprehensive health benefits (including mental health and wellness management account)
  • 20 days of vacation per year upon start
  • Employer contribution of 4% to your retirement savings, with no required employee match
  • Additional compensation totaling 8% of your salary to apply towards additional retirement savings or bonuses (independent of group and individual performance)
  • A team of passionate world-class experts in their field
  • A collaborative and inclusive work environment in our vibrant office space in the heart of Little Italy, in the trendy Mile-Ex district, close to public transportation

Apply