Agentic AI Research

Why This Role Appeals to  

A rare opportunity to work at the intersection of agentic LLMs, multimodal 3D vision, and clinical intelligence.

• Ability to bring contrastive learning, cross-lingual modeling, multimodal alignment, and document understanding into the medical domain.
• Greenfield space: medical agent design is still unexplored compared to 2D VLMs.
• Freedom to publish, open source, and propose new clinical reasoning benchmarks.
• Attractive to researchers who want impact beyond academic settings—directly improving physician workflows and patient outcomes.
• A chance to create India’s first medical foundation-model agent system, setting global standards.
  
  

What We’re Looking For

• Experience developing LLM-based agents, tool-using models, chain-of-thought systems, or orchestrated pipelines.
• Strong background in multimodal learning, vision–language transformers, contrastive models, or clinical NLP.
• Familiarity with medical imaging, radiology workflows, DICOM pipelines, or 3D data representations.
• Expertise in PyTorch/JAX and large-scale training and inference.
• Ability to design safe, interpretable, and auditable reasoning systems.
• Strong publication record in multimodal, medical AI, agentic systems, or LLMs.
• Comfort collaborating with clinicians and biomedical researchers.
  
  

Nice to Have

• Experience with agent frameworks (LangChain, LLaMA Index, Haystack, custom pipelines).
• Background in clinical ontologies, SNOMED, RadLex, or UMLS.
• Contributions to medical AI challenges (BraTS, RSNA, MedVQA, MedIC).
• Prior work in multilingual or code-mixed medical text.
• Proven ability to take research concepts into production-grade systems.
  
  

What We Offer

• Competitive compensation.
• Access to high-compute clusters + large proprietary datasets.
• Full freedom to publish and define development direction.
• Cross-functional collaboration with clinicians, regulatory experts, and product teams.
• A clear path to building systems that meaningfully improve healthcare outcomes.