Machine Learning Scientist, Multimodal AI
Core
Develop and deploy deep learning models integrating imaging, molecular, and clinical data for personalized oncology diagnostics and tumor-informed minimal residual disease testing.
Role type
Senior IC machine learning scientist (multimodal AI)
Builds
Multimodal AI systems integrating H&E whole-slide imaging with genomic, transcriptomic, and cfDNA data for oncology diagnostics
Domain
Biomedical AI / Computational Oncology / Digital Pathology
Deliverable
production ML models
Required skills
Deep learning model development, PyTorch, Python, CNNs, Vision Transformers (ViTs), Sequence Transformers, Representation Learning, Foundation model fine-tuning, Cloud infrastructure management (AWS), Dataset management, Prototyping to production translation
Preferred skills
Multimodal framework integration, DNA/RNA sequencing/methylation/ctDNA assay knowledge, Digital pathology software, Survival/longitudinal modeling, Self-supervised/weakly supervised/MIL learning, Oncology/biomarker domain knowledge, Peer-reviewed publications in ML/bio conferences
Technologies
PyTorch, Python, AWS, CNNs, ViTs, Transformers
Responsibilities
Design and evaluate deep learning models across histopathology, genomics, transcriptomics, and cfDNA; Develop multimodal AI architectures integrating imaging and molecular data; Build scalable production ML workflows; Apply modern ML techniques including CNNs, ViTs, and foundation models; Collaborate to translate prototypes into validated tools; Analyze outputs for biological/clinical insights; Document pipelines and communicate findings
Seniority
Senior, hands-on IC