Research Scientist - VLM Pretraining

Epsilon Health is developing AI technology for medical imaging and diagnostics. The Research Scientist will own pretraining for a radiology report generation model, designing vision-language architectures, multimodal data mixtures, and large-scale training and evaluation for clinical use.

Responsibilities:

• Design, train, and scale vision-language foundation models for radiology applications, owning the pretraining stage end to end
• Develop VLM architectures suited to medical imaging, including native and variable resolution handling, high-resolution tiling, connector design, and token budgets for volumetric studies
• Build and tune multimodal pretraining mixtures across captioning, VQA, grounding, and retrieval tasks, balancing data sources to avoid regressions in language capability
• Develop fine-grained visual grounding during pretraining, enabling models to localize findings within medical images using bounding boxes or segmentation masks
• Own pretraining evaluation (zero- and few-shot transfer, probing, and downstream fine-tunability) — as the signal for base model quality
• Train joint vision-language embedding spaces using contrastive and generative objectives, including region- and sentence-level alignment between images and reports
• Contribute hands-on to all stages of pretraining including dataset curation, architecture design, distributed training, and handoff of base checkpoints to post-training
• Stay current with cutting-edge research in vision-language modeling and large-scale multimodal pretraining
• Drive research and technical excellence through conference publications and technical blog posts, establishing best practices for pretraining medical VLMs at scale