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Image Segmentation Jobs in Ontario (NOW HIRING)

M31 AI

Technical Research Assistant

Toronto, ON · On-site +1

CA$25 - CA$28/hr

GitHub portfolio or publications (optional but encouraged) About M31 M31 Biomedical AI is a biomedical imaging company developing foundation models for medical image segmentation and analysis. Our ...

New

Moneris

Systems Engineer

Toronto, ON · Hybrid

CA$100K - CA$142K/yr

Build pipeline-based deployment patterns for repeatable image delivery across Nutanix, VMware, and ... IPv4, segmentation), identity security, access management, and Public Key Infrastructure (PKI ...

FUJIFILM

Assistant Brand Manager

Mississauga, ON

CA$75K - CA$85K/yr

Social Management - monitor and maintain consistent brand image across various social media ... segments of healthcare, electronics, business innovation, and imaging. We are guided and united by ...

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All JobsImage Segmentation JobsImage Segmentation Jobs in Ontario

Image Segmentation information

See Ontario salary details

$9

$33

$72

How much do image segmentation jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for image segmentation in Ontario is $33.85, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $48.56 per hour, depending on experience, location, and employer.

What is an image segmentation?

An Image Segmentation job involves developing algorithms and models to partition digital images into meaningful regions or objects. Professionals in this role often work with computer vision, deep learning, and artificial intelligence to improve image analysis. Tasks may include data annotation, training machine learning models, and optimizing segmentation accuracy for applications like medical imaging, autonomous vehicles, and industrial automation. Strong programming skills in Python and experience with frameworks like TensorFlow or OpenCV are typically required.

What are the key skills and qualifications needed to thrive in image segmentation, and why are they important?

To excel in Image Segmentation, you need a solid background in computer vision, machine learning, and data annotation, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, OpenCV, TensorFlow, and specialized annotation software is typically required. Attention to detail, collaborative mindset, and effective communication are important soft skills in this position. Mastering these abilities ensures precise segmentation work, efficient teamwork, and contributions to projects in fields such as healthcare, autonomous driving, and digital imaging.

What are the common challenges faced in an image segmentation role?

Professionals in image segmentation often encounter challenges such as dealing with low-quality or ambiguous images, managing large datasets, and ensuring consistency in labeling across various data sources. Staying up to date with rapidly evolving algorithms and tools in computer vision is also important for maintaining best practices. Effective communication with data scientists, engineers, and project managers is key for understanding project requirements and delivering high-quality segmentation results. Overcoming these challenges not only helps produce more accurate models but also contributes to personal skill growth and deeper team collaboration.

What are popular job titles related to Image Segmentation jobs in Ontario?

For Image Segmentation jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Image Segmentation jobs in Ontario look for?

The top searched job categories for Image Segmentation jobs in Ontario are:

Image Segmentation jobs near you
Infographic showing various Image Segmentation job openings in Ontario as of August 2026, with employment types broken down into 67% Full Time, 23% Part Time, and 10% Contract. Highlights an 100% In-person job distribution, with an average salary of $70,418 per year, or $33.9 per hour.

Technical Research Assistant

M31 AI

Toronto, ON • On-site, Remote

CA$25 - CA$28/hr

Full-time

Posted 3 days ago

New

Job description

Read the full description before applying.

MUST HAVE: Experience with deep learning (transformers, CNNs, U-Net), clinical electronic health records (EHR) and/or imaging data.

At M31 Biomedical AI, we are redefining how artificial intelligence understands human health and biology. Our models power universal segmentation and imaging analysis across multiple medical modalities to uncover new biological and clinical insights.

We’re seeking a full-time Research Intern to support biomedical AI research involving clinical EHR (labs, flowsheets, clinical notes) and imaging data (histopathology and radiology). The role will involve running experiments with large-scale foundation models. You’ll be working with a diverse team of AI researchers, clinicians, and computational biologists to explore how deep learning can advance personalized medicine and healthcare for patients.

This position is ideal for someone passionate about biomedical AI, multi-modal data, and collaborative, high-impact research.


What You’ll Do

  • Train deep learning models and run experiments
  • Collaborate with research partners to collect, preprocess, and harmonize structured and unstructured clinical data, pathology and radiology images.
  • Conduct literature search to identify and summarize SOTA architecture and  
  • Work closely with data scientists and clinicians to ensure scientific and clinical relevance
  • Discover, validate and implement new AI tools to improve workflow efficiency
  • Document and maintain reproducible workflows using Git, Python, and cloud-based tools
  • Contribute to publications, internal reports, and presentations summarizing key findings
  • Create clear, compelling presentations and visualizations that translate highly technical results for both clinical and technical audiences

    • Why Join Us

    • Be part of a leading biomedical imaging AI company recognized for its foundational work in universal segmentation
    • Collaborate with top academic and hospital research teams on cutting-edge multi-modal AI projects
    • Gain exposure to large, high-quality datasets spanning medical imaging and clinical data
    • Work in a mission-driven environment that bridges scientific research and real-world healthcare impact
    • Enjoy flexible work arrangements, mentorship, and opportunities for authorship and recognition


    Required Skills & Background

    • Undergraduate degree or currently pursuing a master’s or PhD (or equivalent experience) in Engineering, Computer Science, Mathematics, Biomedical Engineering, Computational Biology or a related field
    • Strong programming experience in Python and ML frameworks (e.g., PyTorch, TensorFlow, MONAI)
    • Strong understanding of deep learning architecture (Transformers, CNNs, U-Net)
    • Background in analyzing biomedical or life science data
    • Understanding of at least one of the following domains:
    • Clinical data (EHR, laboratory results, disease outcomes)
    • Medical imaging (MRI, CT, pathology, etc.)
    • Experience with data management, reproducibility, and collaborative code development
    • Excellent problem-solving, communication, and teamwork skills


    Nice-to-Have

    • Experience with foundation models or large-scale pretraining
    • Biomedical domain knowledge (disease pathophysiology, human anatomy, cellular biology)
    • Experience with agentic coding tools (Claude Code, Codex)
    • Previous work involving multi-institutional datasets
    • Publication record in AI, biomedical imaging, or computational biology


    Application Requirements

    • Resume/CV
    • Cover letter describing your experience and motivation for working on patient-centric clinical foundation models
    • GitHub portfolio or publications (optional but encouraged)


    About M31

    M31 Biomedical AI is a biomedical imaging company developing foundation models for medical image segmentation and analysis. Our technology enables universal understanding of medical images across modalities and institutions.

    We’re now collaborating with leading research partners to extend this vision beyond imaging to include multi-modal clinical data, in order to advance patient healthcare, understand complex diseases and improve therapeutic discovery.

    Job Type: Full-time (12-month renewable contract)

    Location: Hybrid remote – Toronto, ON (M5S 1A8)

    Compensation: CA$25-28/hour, based on experience

    Benefits:

    • Flexible schedule
    • Work-from-home option
    • Mentorship and publication opportunities


    Apply