Machine Learning Software Developer

Overview:
Circle Cardiovascular Imaging (Circle) designs, builds, and implements the best-in-class cardiovascular Magnetic Resonance Imaging solutions. At the heart of everything we do is our unrelenting drive to continually offer better solutions for healthcare providers that improve healthcare outcomes. This fuels our creativity, informs our decisions and it is the reason we are passionate about our work and most importantly why we are successful. We are careful stewards of resources focused on optimizing both customer and investor value. We strive to make Circle a place where employees are highly valued, engaged, and have opportunities for professional development. Our roots are medical and digital, our passion is contagious, and our people are amongst the best.
Circle's vision is to Transform Cardiovascular Care through Intelligent Solutions. Circle is a well-known, established leader in the cardiovascular imaging industry, with our best-in-class MR and CT imaging solutions utilized by top healthcare institutions worldwide.
Position Overview:
This is a critical role for a Machine Learning Engineer who will be a key part of our AI development team. You will take ownership of key components of machine learning systems, driving the design, development, and deployment of robust, scalable models that power our next-generation cardiovascular diagnostic tools. Your primary focus will be on architecting the AI core for the CT and MR based projects across our portfolio. You are a passionate developer who translates complex scientific challenges into production-ready AI solutions.
General Responsibilities:
Architect, build, and deploy high-performance deep learning models for complex tasks, including 3D medical image segmentation, geometric analysis, and physiological prediction.
Write clean, highly-optimized, and thoroughly-tested code in Python.
Serve as a subject matter expert, leveraging your understanding of biomedical data to guide model selection, feature engineering, and validation strategies. Stay at the forefront of the medical imaging AI community (e.g., MICCAI,) to introduce cutting-edge techniques
Partner with senior engineers, scientists, product leaders, and software architects to define technical
requirements and ensure seamless integration of ML models into our broader software ecosystem.
Required Skills/Experience:
3+ years of post-academic, professional experience building deploying machine learning models specifically for biomedical or medical imaging applications.
Deep familiarity with medical imaging standards (DICOM) and specialized libraries
Programming proficiency in Python and/or C++, hands-on experience with at least one major deep learning framework (e.g., PyTorch, TensorFlow).
Proven ability to architect and own end-to-end ML systems, from data ingestion to model deployment.
Strong foundation in software engineering principles, including version control (Git), testing, and
writing clean, maintainable code.
Preferred Skills/Experience:
Demonstrated experience designing and managing ML workflows on a major cloud platform (AWS, GCP, or Azure).
Extensive experience with MLOps tools and methodologies (e.g., Docker, Kubernetes, MLflow, CI/CD
for ML).
Educational Requirements:
PhD in Computer Science, Artificial Intelligence, Data Science, or Masters or equivalent.
About the Benefits:
Competitive compensation and vacation
Transportation allowance
Flexible working arrangements
Employee Wellness Program
Professional development and tuition reimbursement program
Gratifying internal recognition/kudos programs
Annual salary review – based on company and individual performance
Fun, inclusive, ego-free environment where diversity and individual thoughts are encouraged and valued
Upon joining Circle CVI, you will be welcomed into a collaborative and supportive company with uncompromising values on quality, innovation, culture, and customer service. Join us in changing the medical technology world and submit your application below!
#LI-Onsite

Employment type
Full-Time

Work arrangement
No