AI Image Processing Engineer

Cobionix Corporation; Kitchener; Hybrid; CAD 80,000 - 120,000; Full time

Job summary

Cobionix Corporation is seeking an AI Image Processing Engineer to develop deep learning models for medical imaging applications. This role involves working with real-world and synthetic datasets to enhance image processing tasks and ensuring robust model performance in safety-critical environments. The ideal candidate has a background in computer science or robotics and significant experience in AI and robotics integration.

Qualifications

• 3+ years of experience in computer vision or medical imaging.
• Familiarity with preprocessing techniques like denoising and registration.
• Understanding of evaluation methods for imbalanced datasets.

Responsibilities

• Design and train deep learning models for image enhancement and segmentation.
• Build scalable data pipelines for ingesting and augmenting imaging data.
• Collaborate with teams to translate image-based insights into behaviours.

Skills

Deep learning

Computer vision

Python

C++

Robotics

Education

Bachelor’s or Master’s degree in Computer Science, Software, or Robotics Engineering

Tools

PyTorch

TensorFlow

Docker

Kubernetes

Job description

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Extension : Opportunity for contract extension and full-time offer post performance evaluation.

Location : Can be discussed Remote / Hybrid / In-Person

Project Portfolio : Please include a link in your resume

Company Description

At Cobionix, we are pioneering the future of healthcare with our state-of-the-art autonomous robotic platform designed specifically for medical procedures. Our cutting-edge technology integrates advanced robotics to transform medical interventions, making them safer, more precise, and efficient.

About the Role

As an AI Image Processing Engineer , you will develop deep learning models that enable real-time visual perception and decision-making in autonomous robotic systems. You’ll work with both real-world medical imaging data and synthetic datasets generated in high-fidelity simulation environments to train, validate, and deploy models for tasks such as image enhancement, segmentation, and quality assessment. This role bridges simulation and deployment—optimizing models for embedded platforms and ensuring robust performance in dynamic, safety-critical settings. You’ll collaborate across AI, robotics, and clinical teams to help scale intelligent automation into real-world applications.

Responsibilities

• Design and train deep learning models for image enhancement, segmentation, classification, and quality assessment.
• Build scalable data pipelines for ingesting, preprocessing, and augmenting real-world and synthetic imaging data.
• Generate and leverage synthetic datasets using simulation environments for model training and validation.
• Develop real-time inference pipelines optimized for embedded GPU deployment.
• Collaborate with robotics and controls teams to translate image-based insights into adaptive behaviours.
• Define performance metrics and evaluate model accuracy using clinically relevant benchmarks.
• Support model deployment in safety-critical environments, including validation and documentation.
• Contribute to research, publications, and patent filings in the field of imaging AI and autonomous systems.

Required Experience

• Bachelor’s or Master’s degree in Computer Science, Software, Robotics Engineering or a closely related field
• Proficiency in Python / C++ and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• 3+ years of experience developing computer vision or medical imaging models (2D / 3D).
• Familiarity with common preprocessing techniques for imaging data (e.g., denoising, registration, augmentation).
• Strong understanding of evaluation methods for imbalanced datasets and clinical performance metrics.
• Experience building and managing ML pipelines using Docker, Kubernetes, or similar orchestration tools.
• Working knowledge of MLOps best practices including CI / CD for models, experiment tracking, and production monitoring.
• Ability to clearly translate clinical or domain-specific requirements into model objectives.

Nice to Have

• Experience with simulation environments (e.g., Isaac Sim, Gazebo) for generating synthetic imaging data.
• Hands-on work with embedded platforms (e.g., NVIDIA Jetson, Qualcomm RB5) for real-time inference.
• Exposure to reinforcement learning or imitation learning in vision-based robotic tasks.
• Familiarity with medical imaging standards such as DICOM and beam-form data.
• Experience in regulated environments (e.g., ISO 13485, IEC 62304, FDA Good ML Practices).
• Contributions to research publications or open-source medical imaging projects.

This role is designed for someone eager to push the boundaries of what’s possible in medical robotics, providing a unique opportunity to impact the field significantly.

Cobionix Corporation is an equal opportunity employer. We are committed to providing a diverse and inclusive work environment while providing ongoing education for all employees. Qualified applicants will be considered without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We firmly believe that our differences make us stronger.

Please inform us if you require any accommodations during the recruitment process . While we thank all applicants, only those being considered for an interview will be contacted.

Seniority level

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