Senior Applied Research Scientist, Multimodal Foundation Models – Healthcare
Core
Developing longitudinal multimodal foundation models that integrate heterogeneous healthcare data (imaging, EHR, genomics, etc.) for disease progression modeling and precision medicine.
Role type
Senior Applied Research Scientist (Multimodal Foundation Models)
Builds
Medical AI algorithms, foundation models, datasets, and workflows for the healthcare ecosystem.
Domain
Healthcare AI / Multimodal Deep Learning
Deliverable
production ML models
Required skills
Multimodal foundation model development, longitudinal modeling, temporal reasoning, large-scale dataset construction, deep learning framework expertise (PyTorch), scalable research pipeline engineering, agentic AI workflows
Preferred skills
Bridging medical imaging with molecular/biological data (genomics, transcriptomics), distributed GPU training, NVIDIA GPU/AI technologies (CUDA, cuDNN, TensorRT), academic publication record
Technologies
PyTorch, CUDA, cuDNN, TensorRT
Responsibilities
Conduct research on longitudinal multimodal foundation models; Develop novel foundation model architectures and training strategies; Build large-scale datasets, benchmarks, and open-source models; Collaborate with researchers and healthcare partners to translate research into solutions; Publish research in leading venues.
Seniority
Senior, hands-on IC
