Transforming spine surgery through personalized, data-driven solutions by converting raw medical imaging into high-fidelity, clinically accurate 3D models to support surgical planning and improve patient outcomes.
Requirements
- 5+ years of experience developing deep learning models for medical imaging (segmentation, registration, 3D reconstruction).
- Familiarity with regulatory environments such as FDA 510(k) and PCCP.
- Experience with synthetic imaging (GANs, diffusion models).
- Expertise in multi-modal learning and anatomical registration.
- Familiarity with FDA’s Good Machine Learning Practice (GMLP) principles.
Responsibilities
- Lead the development of AI-based segmentation and 3D reconstruction pipelines across CT, MRI, and multi-modal imaging.
- Design and manage model retraining workflows within a regulated framework (e.g., PCCP, 510(k)).
- Build and curate annotated datasets for spinal imaging.
- Champion advanced techniques including self-supervised learning, cross-modal fusion, and generative AI.
- Collaborate with clinical teams to validate anatomical accuracy and ensure real-world impact.
- Oversee model performance evaluation, golden dataset strategy, and toolchain development.
- Build and lead a high-performing team of ML engineers and imaging scientists.
Other
- Ph.D. or M.S. in Biomedical Engineering, Machine Learning, Computer Vision, or a related field.
- Strong understanding of spinal anatomy or orthopedic imaging (preferred).
- Proven leadership in cross-functional teams including clinical, regulatory, and engineering stakeholders.
- This is a fully onsite position in Carlsbad,CA.
- The pay range for this position is $60.00 - $80.00/hr.
- Eligibility requirements apply to some benefits and may depend on your job classification and length of employment.
- Benefits are subject to change and may be subject to specific elections, plan, or program terms.
