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Scientific Machine Learning Jobs in Ontario (NOW HIRING)

Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant ...

To achieve this, we're working on projects that utilize the latest computer science techniques ... As a machine learning engineer, you will be responsible for designing and implementing scalable ...

Graduate degree in Computer Science with a strong background in machine learning required. * Strong problem-solving abilities, solid background in algorithms and data structures required. * Strong ...

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers ...

As a Research Machine Learning Scientist, you will * Join a world-class team of machine learning researchers with an extensive track record in both academia and industry. * Research, develop, and ...

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ... Master or bachelor's degree in computer science, Statistics, Mathematics, Engineering or a related ...

Machine Learning Engineer About Themis Intelligence Themis Intelligence builds the Utility ... A Bachelor's degree in Computer Science, Mathematics, Engineering, Statistics, or a related ...

Machine Learning Engineer

Toronto, ON · Hybrid

CA$152K - CA$174K/yr

Summary: We are currently seeking a Machine Learning Engineer to join our rapidly growing ... Collaborate cross-functionally with engineering, product management, operations and data science to ...

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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 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 July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Machine Learning - Master-Level Internship

Vosyn

Etobicoke, ON • On-site, Remote

$32/hr

Full-time

Re-posted 22 days ago


Job description

Job Title: Machine Learning - Master-Level Internship

Level: Master's Level Internship

Department: Software Development

Duration: 520 Hours (approximately 3 months)

Work location: Remote (with hybrid options in Toronto)

Compensation: Hourly ($32)

The Vosyn internship is unique. Remuneration is equivalent to $32.00 CAD per hour payable in common shares of the Corporation at the then fair market value. For greater clarity, NO cash in-hand (in hourly rate or salary) will be paid to the Intern. Instead, Vosyn being an AI start-up, the upside is in potential future value of said shares based on the hours worked, billed and approved.

About Us: At Vosyn, we embrace the exciting, game-changing world of Artificial Intelligence, driving innovation and pioneering impactful projects across various industries. We are a trailblazing Language Synthesis AI firm reshaping global communication by dissolving language barriers and empowering users. We believe in fostering a culture of flexibility, continuous improvement, and solution-focused strategies. Here, every idea is welcomed, nurtured, and has the potential to scale to new heights. Currently, we're at the forefront of a significant IPO endeavor, truly a unicorn in the making. We invite you to be part of our journey and leave your imprint on the future of AI.

About the Role: We are seeking a talented and motivated Machine Learning Intern to join our team. This role is ideal for a Master's level student passionate about applying machine learning techniques to solve real-world problems. As a Machine Learning Intern, you will work closely with our data scientists and engineers to develop, train, and deploy machine learning models that drive our technology forward.

Key Responsibilities:

  • Assist in designing and implementing machine learning algorithms and models.
  • Collaborate with data scientists to preprocess and analyze data for model training.
  • Evaluate model performance and refine algorithms to improve accuracy and efficiency.
  • Participate in the deployment of machine learning solutions into production environments.
  • Conduct experiments and document findings to support decision-making processes.
  • Stay current with the latest advancements in machine learning and AI technologies.

About You:

  • Currently enrolled or recently graduated from a Master's program in Computer Science, Data Science, Machine Learning, or a related field. Master's program enrollment or completion is mandatory.
  • Strong understanding of machine learning concepts and algorithms.
  • Experience with programming languages such as Python or R.
  • Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Knowledge of data preprocessing and analysis techniques.
  • Excellent analytical and problem-solving skills.
  • Ability to work both independently and collaboratively within a team.
  • Effective communication skills, both written and verbal.

Why Join Us:

  • Be part of the invigorating journey of a start-up transitioning to an IPO.
  • Engage directly with senior management and strategic advisory board members.
  • Enhance your CV with a rich array of experiences unique to Vosyn and AI Venture Lab.
  • Gain hands-on experience contributing to projects that drive growth and make a lasting impact in a fast-paced startup environment.


DEI and Workplace Safety:

At Vosyn Inc., we are committed to fostering a diverse, equitable, and inclusive workplace where every employee feels valued and supported. We believe that diversity of thought, background, and experience enriches our company culture and enhances innovation. We are an equal-opportunity employer and encourage candidates from all walks of life to apply. As part of our commitment to creating a safe and healthy work environment, we prioritize workplace safety, adhering to all relevant regulations and promoting a culture of responsibility. We believe that a safe and inclusive workplace is essential for the well-being and success of our team members. Join us in building a workplace that values diversity, prioritizes equity, and ensures the safety and well-being of every individual.

Recruitment Process:

  1. Application Submission: Candidates are invited to submit their resumes and cover letters through our career portal.
  2. Written Questionnaire: Selected candidates will receive a set of 10 written questions to assess their fit and technical knowledge..
  3. Video Questionnaire: Candidates who successfully pass the written assessment will be asked to answer 10 additional questions to be submitted in a video format to further evaluate their skills and cultural fit. The ability to video record your answers will be required.
  4. Evaluation: Our team will review the responses to both questionnaires. Candidates who meet our criteria will be invited to the next stage.
  5. Orientation Session: Successful candidates will be invited to participate in an orientation session where they will learn more about Vosyn, our projects, and what to expect during the internship. After this session, you will be given the opportunity to opt-in if you believe that this internship is for you.

Please note that only candidates who apply through our website will be contacted.

At Vosyn, we hire on a rolling basis, so we encourage you to apply as soon as possible. While we operate with flexibility, we also cater to academic semester work terms to align with school schedules, ensuring a smooth transition for students joining us.

Be a part of a fast-growing global organization that values diversity of thought, experience, and culture. Our interns come from top universities worldwide, and we invite you to contribute, learn, and grow with us on this exciting journey.


Apply Now:
Vosyn Careers

Employment Type: FULL_TIME