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Medical Imaging Machine Learning Jobs in Ontario

Altis Labs

CA$175K - CA$300K/yr

Design and implement deep learning architectures for 3D volumetric medical imaging (CT, PET, MRI ... PhD in machine learning, computer vision, statistics, or a related field preferred; exceptional ...

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine Learning Engineer Position: Full time Location: Toronto, Ontario (Initially Remote) About ... We offer a full comprehensive benefits package including medical, dental and vision. Employees ...

Tubi

CA$143K - CA$205K/yr

About The Role The Machine Learning team at Tubi drives the innovation behind personalized user ... including medical, dental, vision insurance, vacation/paid time off and other benefits in ...

United Airlines

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$105K - CA$125K/yr

The role of a machine learning professional involves applying machine learning techniques and ... Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) * Retirement ...

Pleora

Software Developer

Kanata, ON

CA$80K - CA$120K/yr

... medical imaging applications with 25 years of expertise in vision applications with our growing ... Develop software applications for video switching, machine learning, industrial inspection and ...

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Medical Imaging Machine Learning information

See Ontario salary details

$22.5K

$91.5K

$193K

How much do medical imaging machine learning jobs pay per year?

As of Aug 31, 2026, the average yearly pay for medical imaging machine learning in Ontario is $91,529.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What is a medical imaging machine learning?

A Medical Imaging Machine Learning job involves developing and applying artificial intelligence (AI) techniques to analyze medical images, such as X-rays, MRIs, and CT scans. Professionals in this field use machine learning models to assist in disease detection, diagnosis, and treatment planning. They work with large medical datasets, optimize deep learning models, and collaborate with radiologists and healthcare professionals to improve diagnostic accuracy and efficiency. The role requires expertise in machine learning, computer vision, and medical imaging technologies.

What are the key skills and qualifications needed to thrive in medical imaging machine learning?

To excel in Medical Imaging Machine Learning, a solid background in computer science, machine learning, and image processing, often supported by an advanced degree (MS or PhD) in a related field, is essential. Experience with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and familiarity with medical imaging standards (like DICOM) are commonly required. Strong analytical thinking, problem-solving abilities, and the ability to communicate complex technical concepts to multidisciplinary teams are highly valued. These competencies enable professionals to develop and implement effective AI solutions that enhance diagnostic accuracy and workflow efficiency in healthcare settings.

What types of teams do medical imaging machine learning professionals typically work with, and how is collaboration structured?

Medical Imaging Machine Learning specialists often collaborate closely with radiologists, data scientists, software engineers, and clinical researchers to develop and refine AI-driven diagnostic tools. The work environment is usually multidisciplinary, involving regular meetings, code reviews, and joint problem-solving sessions to ensure alignment between technical solutions and clinical needs. Team members may also work with regulatory experts to ensure compliance with healthcare standards. This collaborative approach ensures that models are both technically robust and clinically relevant, ultimately supporting better patient outcomes.

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

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

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

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

Medical Imaging Machine Learning jobs near you
Infographic showing various Medical Imaging Machine Learning job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 21% Part Time, and 6% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $91,529 per year, or $44 per hour.

Senior Machine Learning Scientist (CA)

On-site

Altis Labs
See more jobs at Altis Labsexternal

CA$175K - CA$300K/yr

Full-time

Medical, Dental, Vision

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

Job description

What We Do

We build AI models to enable smaller, faster, and more successful clinical trials.

What We Do

We build AI models to enable smaller, faster, and more successful clinical trials.

About Altis Labs

Altis Labs is a computational imaging company focused on improving how oncology trials measure treatment benefit. Our core technology is IPRO, an AI model that generates patient-level outcome predictions directly from routine medical imaging data. Our global biopharma customers use IPRO to predict efficacy, navigate billion-dollar development decisions with confidence, and move their most promising therapies through Phase I–III trials faster. IPRO is trained on the industry’s largest real-world imaging, clinical, and outcomes database, containing over 210 million longitudinal images and more than one million patient-years of linked outcomes.

Our multidisciplinary team of AI scientists, clinicians, and business operators is on a mission to get the most effective treatments to patients sooner. We collaborate closely with academic medical centers and co-publish our results at top-tier medical conferences.

Altis is headquartered in Toronto, serves 6 of the top 20 global biopharmaceutical companies, and is backed by leading life sciences and technology investors.

What Makes This Role Compelling
  • Unusually rich data: Access to large, diverse patient datasets with longitudinal outcomes across multiple cancer types
  • Novel methodology: We're developing approaches that push beyond standard practices in medical imaging AI
  • Multi-cancer generalization: Building methods that transfer across cancer types, not one-off solutions
Responsibilities & Expectations
  • Design and implement deep learning architectures for 3D volumetric medical imaging (CT, PET, MRI)
  • Develop survival models that handle censored outcomes, competing risks, and the statistical nuances of time-to-event prediction
  • Optimize training pipelines to efficiently process large-scale imaging datasets on cloud GPU infrastructure
  • Collaborate with our ML team to establish best practices and push the state of the art
  • Contribute to research publications and present findings at conferences
Qualifications
  • 7+ years of experience in machine learning, with substantial work in computer vision or medical imaging
  • PhD in machine learning, computer vision, statistics, or a related field preferred; exceptional industry track record considered
  • Deep expertise in 3D vision—experience with volumetric architectures (3D CNNs, Vision Transformers for 3D data, etc.)
  • Strong foundation in survival analysis and time-to-event modeling (Cox models, deep survival models, competing risks)
  • Proven ability to train large models efficiently at scale—you understand distributed training, memory optimization, and what it takes to iterate quickly on big data
  • Proficiency with PyTorch and modern ML infrastructure
  • Track record of impactful research (publications, deployed systems, or equivalent demonstrations of technical depth)
Nice To Have
  • Experience with medical imaging foundation models or self-supervised learning on unlabeled imaging data
  • Background in uncertainty quantification: calibrated predictions, conformal prediction, Bayesian deep learning
  • MLOps experience: productionizing models, CI/CD for ML, model monitoring
  • Familiarity with oncology, radiology, or regulated healthcare environments
Benefits
  • Competitive pay and generous equity participation
  • Coverage for medical, vision, and dental insurance
  • 4 weeks of vacation per year

Compensation Range: CA$175K - CA$300K

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