Senior AI Research Scientist

About the role

iCAD is a global leader on a mission to create a world where cancer can't hide by providing clinically proven AI‑powered solutions that enable medical providers to accurately and reliably detect cancer earlier and improve patient outcomes. Its industry‑leading ProFound Breast Health Suite offers AI‑powered mammography analysis for breast cancer detection, density assessment, and risk evaluation, cleared by the FDA, CE marked, and licensed by Health Canada, used by thousands of providers serving millions of patients in over 50 countries. iCAD is seeking a Senior AI Research Scientist to join its dynamic R&D team. In this role you will design, develop, and improve AI‑based medical devices that drive the next generation of solutions in medical imaging and healthcare, particularly in breast cancer detection and diagnosis, working in a fast‑paced environment with cutting‑edge technology while directly contributing to saving lives through improved healthcare solutions.

Responsibilities

• Design, develop, and optimize AI/ML models, specifically deep learning algorithms, to advance breast cancer detection and imaging tools.
• Conduct research to identify new methodologies, techniques, and technologies in AI/ML applicable to medical image analysis.
• Collaborate with Product Management to identify key innovation areas where AI can drive meaningful product functionality and market differentiation.
• Contribute to strategic roadmaps by providing insights on AI trends and potential research breakthroughs that align with customer needs and business goals.
• Work with large medical datasets, performing data preprocessing, annotation, and enhancement tasks to improve AI model accuracy and efficiency.
• Partner with software engineers, radiologists, clinical teams, and other stakeholders to integrate AI solutions into production environments and evaluate real‑world performance.
• Lead testing and validation of AI models to ensure they meet regulatory standards (including FDA clearance) and are robust for clinical use.
• Provide write‑ups, white papers, and technical documentation describing the functionality, benefits, and impact of AI models and innovations.
• Collaborate with Product Management and Marketing teams to highlight key benefits of research deliverables for external audiences, including customers, investors, and healthcare professionals.
• Provide mentorship and guidance to junior researchers and collaborate with cross‑functional teams to accelerate R&D efforts.
• Ensure all AI development activities comply with healthcare industry regulations and are accompanied by supporting documentation for regulatory submissions.

Requirements

• Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 5+ years of R&D experience in medical imaging, computer vision, or machine learning, with a proven track record of developing AI solutions.
• Expertise in deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Advanced knowledge of Python and C++ for implementing AI solutions.
• Demonstrated experience with large‑scale data processing and managing complex datasets.
• Experience with medical imaging datasets (e.g., DICOM, mammography, CT, MRI) is highly preferred.
• Solid understanding of AI model validation techniques, regulatory requirements (e.g., FDA 510(k)), and experience working in a healthcare environment.
• Strong publication history in top‑tier conferences and journals, showcasing original research.
• Strong communication skills, with the ability to present complex research results to technical and non‑technical stakeholders.
• Excellent analytical, organizational, and communication skills with the ability to present complex ideas clearly.
• A proactive team player, capable of working independently while contributing to cross‑functional teams.
• Ability to generate patentable ideas and contribute to intellectual property development.

Qualifications

• Experience with explainable AI (XAI) and model interpretability in medical applications.
• Familiarity with cloud platforms (Google Cloud, AWS) and deploying AI solutions in cloud environments.
• Knowledge of biostatistics, healthcare regulations, and clinical workflows.
• Experience working in cross‑functional teams and fast‑paced R&D environments.