Cleerly is seeking to revolutionize heart disease diagnosis and treatment through AI-driven precision diagnostic solutions. The Principal Machine Learning Scientist will lead the development, validation, and deployment of advanced machine learning models to improve diagnostic and prognostic care pathways for heart disease, aiming to prevent heart attacks.
Requirements
- 8+ years of post Ph.D. or industry experience leading applied ML initiatives.
- Demonstrated technical leadership in developing and deploying ML models in regulated or clinical domains. Recognized expert in machine learning and medical imaging.
- Deep expertise in machine learning theory and practice, with a strong track record in 3D medical image analysis, including segmentation, reconstruction, registration, restoration, detection, and/or predictive analytics.
- Strong track record of publications in top-tier machine learning, medical imaging or computer vision
- Hands-on expertise in advanced ML techniques such as vision transformers, self-supervised learning, continual/incremental learning, contrastive learning or physics-informed deep learning.
- Experience with ML orchestration frameworks, such as Kubeflow, MLFlow, Ray, Metaflow, or Argo Workflow
- Strong domain knowledge in cardiac CT and coronary artery disease diagnostics.
Responsibilities
- Lead the design and development of state-of-the-art ML and deep learning models for complex, multi-modal medical imaging and clinical data across multiple projects
- Define technical and research strategies to achieve new business opportunities, and lead proposals to pursue new areas of science or technology in programs to meet the organization’s long-term strategic goals.
- Set the technical direction for core ML initiatives, balancing scientific rigor with clinical and business priorities. Evangelizes new technology within the company.
- Drive innovation in data representation, model architecture, and learning paradigms to advance the field and improve clinical outcomes. Establish frameworks and processes that are used across teams.
- Oversee and guide rigorous validation, benchmarking, and regulatory-aligned evaluation of ML algorithms.
- Partner with scientific affairs, engineering, product, biostatistician, and regulatory teams to drive the end-to-end lifecycle of medical products to ensure successful delivery and impact. Rally others around a clear vision.
- Provide support and guidance in all phases of the product development cycle to ensure delivery of high-quality products. Provide design and system optimization solutions to drive improved customer experience and satisfaction.
Other
- Ph.D. in Computer Science, Biomedical Engineering, Data Science, or a related technical field.
- Provide technical leadership across multidisciplinary teams
- Help shape the company’s ML roadmap, and guide high-stakes projects from ideation through regulatory approval and clinical integration.
- Represent the company in strategic research collaborations with leading academic and clinical institutions, driving innovation at the intersection of AI and cardiovascular health.
- Mentor and guide other ML scientists and engineers, fostering a culture of technical excellence and continuous learning.
