Senior Computer Vision and Medical Image Processing Engineer – Canada

Job Title: Senior Computer Vision and Medical Image Processing Engineer

Job Type: Full-time

Location: Montreal

Start date: January, 2024

About Us:

YULCOM Technologies is a Montreal-based multinational consulting firm that specializes in information technology, systems integration, and artificial intelligence solutions. YULCOM specializes in web design, software development, web packages and web and mobile applications. It supports its customers in integrating the best digital technologies and improving their process management in North America, Europe, Africa and Asia.

Responsibilities:

1-Develop and Implement Computer Vision Algorithms:

• Design and implement advanced computer vision algorithms for the analysis of medical images, with a focus on X-ray and ultrasound modalities.
• Utilize machine learning techniques for image segmentation, feature extraction, and pattern recognition.
• Implement algorithms specifically geared towards finding and characterizing nodules to facilitate clinical interpretation of medical images.
• Collaborate closely with medical professionals to understand clinical needs and ensure that the algorithms contribute to accurate and meaningful findings.

X-ray and Ultrasound Image Processing:

• Specialize in the analysis and processing of X-ray and ultrasound images.
• Develop and optimize image processing pipelines for enhancing image quality, artifact reduction, and extracting relevant information.

Proposition for a PACS Integration

• Possess expertise in integrating computer vision solutions with PACS (Picture Archiving and Communication System) technology.
• Collaborate with the IT team to ensure seamless integration into existing healthcare systems, emphasizing data warehousing best practices.

Edge and Cloud Integration:

Implement solutions for both edge and cloud-based environments, ensuring efficient processing and storage of medical imaging data.

Architect and optimize image processing workflows for edge devices and cloud platforms.

Data Warehousing:

• Design and implement robust data warehousing solutions for medical imaging data, ensuring scalability, security, and accessibility.
• Collaborate with the data engineering team to establish best practices for storing and retrieving medical images.

Algorithm Optimization:

• Optimize algorithms for real-time processing and large-scale datasets, ensuring efficient implementation on various platforms.
• Collaborate with hardware and software teams for seamless integration.

Research and Development:

• Stay current with the latest advancements in computer vision and medical image processing, with a focus on edge and cloud technologies.
• Lead research initiatives to explore and implement innovative solutions specific to X-ray and ultrasound imaging, PACS integration, and data warehousing.

Cross-functional Collaboration:

Collaborate with multidisciplinary teams, including software engineers, data scientists, and medical professionals, to understand requirements and refine solutions.

Documentation and Reporting:

Document algorithms, methodologies, and results comprehensively.

Prepare and deliver reports and presentations to stakeholders.

Qualifications:

• Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Proven experience in developing and implementing computer vision algorithms, with a focus on X-ray and ultrasound image processing.
• Strong programming skills in languages such as Python, C++, or Java.
• Proficiency in using popular computer vision and machine learning libraries (e.g., OpenCV, TensorFlow, PyTorch).
• Experience with PACS technology integration.
• Experience with data warehousing for medical imaging data.
• Familiarity with edge and cloud computing technologies.
• Strong problem-solving skills and the ability to work independently and as part of a team.
• Excellent communication and collaboration skills.

Preferred Skills:

• Familiarity with regulatory standards and compliance in the healthcare industry.
• Knowledge of GPU programming for parallel computing.