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Tier-1 brand, mid-level generalist title, metro location, and common skillset increase candidate competition.
Specialized medical imaging, regulatory knowledge, and clinical collaboration make background fit highly industry-specific.
Explicit 5+ years, PhD/master's, required medical imaging expertise and regulatory compliance create strict filters.
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Lead end-to-end development of deep learning models for medical imaging including data preprocessing, training, evaluation, and deployment.
Explore and fine-tune foundation models like vision transformers and multimodal models for diagnostic and clinical imaging applications.
Collaborate cross-functionally to ensure clinical relevance, scalability, regulatory compliance, and contribute to scientific publications and mentorship.
PhD or master’s degree in computer science, Biomedical Engineering, Applied Mathematics, or related field.
5+ years experience in data science or machine learning with at least 3 years focused on medical imaging.
Strong experience with deep learning frameworks (TensorFlow, PyTorch) and foundation models including prompt engineering and domain adaptation.
Office-based role requiring at least 3 days per week onsite presence.
Experienced in developing AI solutions for medical imaging with hands-on expertise in 2D/3D medical image datasets and toolkits such as MONAI or SimpleITK.
Proficient in healthcare data compliance standards (HIPAA, FDA, MDR) and medical device AI/ML lifecycle management.
Capable of driving research innovation and mentoring junior data scientists in a cross-disciplinary environment involving radiologists, regulatory teams, and engineers.