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Scientific Machine Learning Jobs in Ontario (NOW HIRING)

Machine Learning Application * Convert data science prototypes into robust, scalable ML solutions. * Apply appropriate ML algorithms to structured and unstructured data problems. * Evaluate model ...

Machine Learning Application * Convert data science prototypes into robust, scalable ML solutions. * Apply appropriate ML algorithms to structured and unstructured data problems. * Evaluate model ...

Machine Learning Application * Convert data science prototypes into robust, scalable ML solutions. * Apply appropriate ML algorithms to structured and unstructured data problems. * Evaluate model ...

Machine Learning Application * Convert data science prototypes into robust, scalable ML solutions. * Apply appropriate ML algorithms to structured and unstructured data problems. * Evaluate model ...

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Minimum three years of experience delivering major data science projects in large, complex ... Strong technical skills: machine learning, data engineering, MLOps, cloud solution architecture ...

Educational Background: BS or MS in Computer Science, or related field * MLOps Experience: 3+ years of hands-on experience in DevOps and MLOps, with a focus on deploying and managing machine learning ...

Showing results 21-40

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 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 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 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 Ontario?

For Scientific Machine Learning jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Ontario look for?

The top searched job categories for Scientific Machine Learning jobs in Ontario are:

Infographic showing various Scientific Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Full-time

Re-posted 11 days ago


Job description

Job Description

At RBC Borealis, you'll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.

We're looking for an enthusiastic Machine Learning Researcher who's excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a Machine Learning Researcher, you're looking to channel your love of playing with real-world data into industry-disrupting solutions. We're a lab that supports research on a wide variety of theoretical and applied machine learning projects. Working in our lab will grant you unique access to massive structured and unstructured datasets with the tools and resources necessary to build game-changing statistical models.

Being part of our team means you'll also have the opportunity to publish original research in peer-reviewed academic journals and participate in conferences around the world, such as NeurIPS, ICLR, ICML, CVPR and more.

Your responsibilities include:

  • Developing novel AI solutions that facilitate impactful products;

  • Conducting original, publishable research by advancing the state-of-the-art in machine learning techniques;

  • Working with the development team to transfer research work into production;

  • Interpreting larger organizational needs and designing algorithmic solutions that can drive the next generation of banking experiences;

  • Identifying relevant new AI technologies as they become available, and disseminating them into the bank's technology capabilities.

You're our ideal candidate if you have:

  • A passion for solving open problems using data and algorithms;

  • A PhD in a sub-area of AI or demonstrated research track record by means of publications and/or sophisticated AI product experience;

  • Ability to formulate and drive a research project independently without close supervision;

  • Proficiency in Python and Deep Learning packages such as Tensorflow or PyTorch.

What's in it for you?

  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

  • Leaders who support your development through coaching and managing opportunities;

  • Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo, and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

#Ll-POST

Job Skills

Analytical Thinking, Decision Making, Detail-Oriented, Long Term Planning, Machine Learning (ML), Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations, Research Documents

Additional Job Details

Address:

401 GEORGIA ST W:VANCOUVER

City:

Vancouver

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2025-11-25

Application Deadline:

2026-10-05

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME