Applied AI Health Scientist

What you'll do

• Manage the full lifecycle of AI system development including data curation, model training, and clinical deployment.
• Review and evaluate AI/ML technical proposals and deliverables from external teams for risks and weaknesses.
• Provide guidance on model development, training methods, and validation strategies to ensure clinical applicability.
• Advise on the integration of multimodal health data including EHR, imaging, and genomic data.
• Assess model architectures to ensure alignment with program goals and clinician workflows.
• Evaluate benchmarking results and provide feedback on the methodological soundness of AI models.
• Produce high-quality reports and presentations synthesizing complex technical findings for senior decision makers.
• Advise on deployment considerations such as interpretability, reliability, and safety in real-world settings.

What we're looking for

• Master’s degree in a Computer Science, Machine Learning, or Data Science field.
• 5+ years of experience with Applied AI in the Health domain.
• Experience applying advanced ML methods, including LLMs or deep learning, to complex health datasets like EHR, genomic, and imaging data.
• Experience in evaluation methods for AI/ML, including robustness, fairness, interpretability, and reproducibility.
• Experience in interacting and communicating with senior-level executives, including SES or GS-15.
• Ability to review, critique, and guide AI/ML technical work.
• Experience with the rare disease field (preferred).
• Doctorate degree in Computer Science, Machine Learning, Data Science, or related field (preferred).