Develop algorithms combining deep learning, computational geometry, and medical imaging
Build and optimize 3D segmentation, modeling, and measurement pipelines for clinically relevant workflows
Design, train, and validate deep learning models and geometry-based methods for integration into a cloud-based healthcare platform
Collaborate with Product and Engineering teams to translate clinical and business needs into robust algorithm designs
Work with Clinical, Regulatory, and Quality teams to ensure compliance with medical software development standards
Continuously improve algorithm accuracy, robustness, and computational efficiency
Contribute to research activities and exploration of new methods in AI and medical imaging

At least 3 years of experience developing deep learning models and computational geometry algorithms
Experience deriving measurements and features from 3D segmentations
Strong software development skills, especially in Python
Background in medical image analysis (CT, MRI, ultrasound, or similar modalities)
Experience with 3D data processing, mesh handling, and geometric feature extraction
Hands-on experience with frameworks and libraries such as NumPy, SciPy, and PyTorch
Solid understanding of algorithm optimization, numerical stability, and rigorous validation methodologies
Ability to work effectively in cross-functional teams
Strong communication skills and proactive approach
Nice to have: Experience with TypeScript
Familiarity with AWS-based cloud environments and products
Experience with VTK or similar 3D visualization and processing frameworks
Understanding of medical software development processes and standards
Research background or interest in advanced AI and imaging methods

Senior/Lead Computer Vision Engineer

Key skills