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Medical Machine Learning Internship Jobs in Ontario

CA$75K - CA$141K/yr

Exposure to machine learning, generative AI, or large language models through coursework, projects, or internships. * Experience with containers and orchestration technologies such as Docker and ...

Research Scientist, Learnable Planner

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Qualifications: - MS/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... internships, work experience, research projects, and papers at top conferences. - Strong ...

Research Scientist

Toronto, ON · On-site

CA$158K - CA$269K/yr

Qualifications: - Masters/PhD degree in Computer Science, AI, Machine Learning, Computer Vision ... internships, work experience, research projects, and papers at top conferences. - Strong ...

... AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study. - Demonstrated research/software engineering experience: through previous internships, work experience ...

Research Scientist, Simulation Agents

Toronto, ON · On-site +1

CA$158K - CA$269K/yr

Qualifications: - Masters/PhD in machine learning, computer science, engineering, or a related ... Medical, Dental and Vision coverage (for full-time employees only). - Unlimited Vacation ...

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related ... Medical, Dental and Vision coverage (for full-time employees only). - Unlimited Vacation ...

Delivery Engineer - Canada

Toronto, ON · On-site

CA$80K - CA$120K/yr

Exposure to real-time computing, big data technologies, or machine learning through coursework, internships, or project experience is a plus. Benefits 1. Health Insurance, PTO, stock option 2. The ...

Showing results 21-40

Medical Machine Learning Internship information

What is a medical machine learning internship?

A Medical Machine Learning Internship is a temporary position where students or recent graduates work on projects that apply machine learning techniques to healthcare and medical datasets. Interns typically collaborate with data scientists, clinicians, and researchers to develop algorithms that can assist in diagnosing diseases, predicting patient outcomes, or improving healthcare processes. This role provides hands-on experience with real-world medical data, exposure to regulatory considerations, and the opportunity to contribute to impactful healthcare innovations. Such internships help interns build technical and domain-specific skills, preparing them for future careers in medical data science.

What kinds of projects and responsibilities can I expect during a medical machine learning internship?

As a Medical Machine Learning Intern, you'll typically work on real-world datasets to develop, test, and refine machine learning models aimed at improving healthcare outcomes. Your daily tasks may include data preprocessing, feature engineering, model selection, and performance evaluation under the guidance of experienced data scientists or clinicians. Collaboration is key, as you'll often work with multidisciplinary teams, including software engineers, clinicians, and researchers. This hands-on experience allows you to gain practical skills and contribute to impactful projects that can enhance patient care or medical research.

What are the key skills and qualifications needed to thrive as a medical machine learning intern, and why are they important?

To thrive as a Medical Machine Learning Intern, you need a solid background in statistics, programming (Python or R), and foundational knowledge of machine learning algorithms, typically supported by coursework or a relevant degree in computer science, engineering, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience working with medical datasets or healthcare IT systems are highly valued. Strong analytical thinking, attention to detail, and effective communication skills will help you collaborate with interdisciplinary teams and present findings clearly. These skills are crucial for developing accurate, impactful models that address real-world healthcare challenges and ensure patient safety.

What are popular job titles related to Medical Machine Learning Internship jobs in Ontario?

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

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

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

What cities in Ontario are hiring for Medical Machine Learning Internship jobs?

Cities in Ontario with the most Medical Machine Learning Internship job openings:

Cloud/AI Platform Engineer

BMO

On-site

CA$75K - CA$141K/yr

Full-time, Part-time

Medical, Life, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

AI Platform Engineer (New Graduate)

Location: Toronto, ON (Hybrid)

Job Type: Full-Time

Experience Level: New Graduate / Entry Level

About The Role

Are you looking to make your mark in AI? Are you an AI thought leader? We are seeking a passionate and curious AI Platform Engineer (New Graduate) to help build, operate, and scale the next generation of AI infrastructure and platforms. This role is ideal for recent university graduates who are excited about cloud computing, artificial intelligence, machine learning platforms, developer tools, and large-scale distributed systems. It’s an opportunity that can make you an AI leader at BMO. As an AI Platform Engineer, you will work with experienced engineers and data scientists to create reliable, secure, and scalable platforms that enable AI applications and machine learning workloads across the organization. This is an opportunity to learn from industry experts while contributing to cutting‑edge AI solutions that drive real business impact.

What You'll Do
  • Build and maintain cloud‑native platform services that support AI and machine learning workloads.
  • Design and implement automation solutions using Infrastructure as Code (IaC).
  • Develop tools, APIs, and services that improve developer productivity and platform reliability.
  • Assist in deploying, monitoring, and scaling AI models and machine learning pipelines.
  • Collaborate with software engineers, data scientists, and product teams to operationalize AI solutions.
  • Monitor platform health and troubleshoot performance, reliability, and scalability issues.
  • Contribute to CI/CD pipelines and DevOps practices for AI and platform engineering teams.
  • Participate in system design discussions and code reviews.
  • Learn and apply best practices around security, observability, governance, and cloud architecture.
Qualifications
  • Required
    • Bachelor’s or Master’s degree in Computer Science, Software Engineering, Computer Engineering, Data Science, or a related technical field completed within the last 12 months.
    • Strong programming skills in one or more languages such as:
      • Python
      • Go
      • Java
      • C#
    • Understanding of software engineering fundamentals, including:
      • Data structures and algorithms
      • Object‑oriented design
      • REST APIs
      • Version control (Git)
    • Familiarity with Linux operating systems and scripting.
    • Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
    • Strong problem‑solving and analytical skills.
    • Excellent communication and collaboration abilities.
  • Preferred
    • Exposure to machine learning, generative AI, or large language models through coursework, projects, or internships.
    • Experience with containers and orchestration technologies such as Docker and Kubernetes.
    • Familiarity with MLOps concepts and tools.
    • Understanding of CI/CD practices and automation.
    • Experience with infrastructure‑as‑code tools such as Terraform.
    • Contributions to open‑source projects, hackathons, research, or personal technical projects.
What You'll Learn
  • AI platform architecture and operations at scale.
  • Cloud‑native application design and deployment.
  • MLOps, LLMOps, and AI governance best practices.
  • Platform engineering and site reliability engineering principles.
  • Secure software development and enterprise cloud operations.
What We’re Looking For
  • Are naturally curious and eager to learn.
  • Enjoy solving challenging technical problems.
  • Thrive in collaborative environments.
  • Take ownership of their work and seek continuous improvement.
  • Are excited about the future of AI and cloud technologies.
  • Critical Thinking
  • Building and managing relationships.
  • Adaptability.
  • Verbal & written communication skills.
  • Collaboration & team skills.
  • Analytical and problem solving skills.
  • Data driven decision making.
Nice-to-Have Technical Skills
  • Azure AI Services, Azure Machine Learning, or Azure Kubernetes Service (AKS)
  • Kubernetes, Docker, Helm
  • Terraform or Bicep
  • GitHub Actions or Azure DevOps
  • Prometheus, Grafana, OpenTelemetry
  • PostgreSQL, Redis, or NoSQL databases
  • LangChain, Semantic Kernel, or other AI frameworks
  • Retrieval-Augmented Generation (RAG) concepts.
Salary

$75,900.00 - $141,900.00

The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part‑time roles will be pro‑rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance‑based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:

Pay Type

Salaried

The above represents BMO Financial Group’s pay type for this position.

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in‑depth training and coaching, to manager support and network‑building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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BMO logo

About BMO

Sourced by ZipRecruiter

BMO, or Bank of Montreal, is one of the biggest multinational banking and financial services corporations in North America. Developed in 1817, BMO's American headquarters are located ideally in Chicago, Illinois while its main world headquarters are situated in Montreal. The bank operates in a multitude of sectors including personal and commercial banking, wealth management and investment banking products and solutions. Over the years, BMO has been recognized for its commitment to doing what's right for its customers, employees, and society.

Industry

Banking and credit intermediation

Company size

5,001 - 10,000 Employees

Headquarters location

Chicago, IL, US

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