Senior Machine Learning Software Developer (2026-025)

Circle Cardiovascular Imaging•Calgary, AB

7d•Onsite

About The Position

We are seeking a Senior Machine Learning Software Developer to play a key role in the design, development, and delivery of advanced AI systems for cardiovascular imaging applications. This role is suited for an experienced, self-directed developer with deep expertise in medical image processing, machine learning, and production software development. The Senior Machine Learning Software Developer will report to the Director, Artificial Intelligence Development.

Requirements

4+ years of post-academic professional experience designing, building, and deploying machine learning systems for biomedical, medical imaging, or related scientific applications.
Strong experience with medical imaging data, standards, and workflows, including DICOM and relevant medical imaging libraries or toolkits.
Proven ability to architect, implement, and own end-end ML systems, from data ingestion and preprocessing through training, validation, deployment, and monitoring.
Advanced programming skills in Python and/or C++, with hands-on experience using at least one major deep learning framework such as PyTorch or TensorFlow.
Strong understanding of deep learning methods for medical imaging, including segmentation, classification, registration, reconstruction and geometric modeling.
Demonstrated ability to work independently on complex technical assignments with minimal supervision.
Strong software engineering foundation, including Git-based version control, automated testing, code review, documentation, debugging, and clean code practices.
Ability to evaluate the downstream impact of design and implementation choices on other projects, systems, and product teams.
Clear communication skills, with the ability to explain technical decisions, trade-offs, and risks to both technical and cross-functional stakeholders.

Nice To Haves

Experience with scalable ML infrastructure, model serving, experiment tracking, data pipelines, containerization, or MLOps practices.

Responsibilities

Design, implement, and deploy high-performance deep learning models for complex biomedical imaging tasks, including 3D medical image segmentation, geometric analysis, registration, and related applications.
Take ownership of large ML software components or scientific modules, including architecture, implementation, optimization, validation, and integration into production workflows.
Develop clean, efficient, well-tested code in Python and/or C++, with a strong focus on maintainability, scalability, and software engineering best practices.
Work independently on challenging technical problems, evaluate trade-offs, and make recommendations that influence project direction, system design, and implementation strategy.
Contribute to high-impact research and development efforts, including work that may lead to publications in peer-reviewed conferences such as MICCAI, ICLR, CVPR or similar venues.
Mentor junior developers and researchers on software development practices, ML engineering workflows, medical imaging challenges, and model validation standards.
Stay current with advances in medical imaging AI, deep learning, and scientific software development, and introduce relevant methods into the team’s technical roadmap.