Machine Learning Scientist- AI Imaging

We are seeking a highly motivated Machine Learning Scientist with deep expertise in AI-driven image analysis to join our interdisciplinary team advancing precision therapeutics and diagnostics. You will lead the development and deployment of machine learning models that integrate histopathology imaging data (H&E-stained slides) with multi-modal biomarkers, driving clinical and scientific insights across large-scale cancer datasets. You’ll work closely with scientists, pathologists, and engineers to innovate and apply deep learning approaches—including convolutional neural networks (CNNs) and vision transformers (ViTs)—to predict clinical outcomes, recurrence risk, and biological phenotypes from digital pathology images. Responsibilities include designing, implementing, and evaluating deep learning models trained on high-resolution histopathology images; developing multi-modal architectures that integrate H&E-stained slide data with genomic, transcriptomic, and ctDNA-based features; contributing to the development of production-quality machine learning pipelines using AWS cloud infrastructure; building scalable training workflows to handle tens of thousands of whole-slide images with automated pre-processing, tiling, and data augmentation; collaborating with cross-functional teams; and communicating results through well-documented code, internal presentations, and peer-reviewed publications.