Research Scientist - VLM Pretraining

Epsilon Health is tackling critical challenges in medical imaging and diagnostics by leveraging advanced AI technologies. They are seeking a Research Scientist with expertise in large-scale vision-language pretraining to develop multimodal models for clinical use in radiology, overseeing the pretraining stage of their radiology report generation model.

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