Duration

3–6 Months (Extension / PPO based on performance)

About the Role

We are looking for GenAI Interns passionate about applying Large Language Models (LLMs) and AI agents to real-world medical imaging workflows such as radiology reporting, clinical summarization, decision support, and enterprise viewers.

You will work closely with product, engineering, and clinical SMEs to build production-grade AI features for RIS, PACS, VNA, and reporting platforms.

Key Responsibilities

🔹 GenAI & LLM Development

• Build and fine-tune LLM-based pipelines for:

  • Radiology report generation & structuring

  • Clinical summarization from imaging + text inputs

  • Follow-up recommendations and impression drafting

• Implement prompt engineering, RAG (Retrieval Augmented Generation), and agentic workflows

• Integrate LLMs with structured + unstructured medical data

🔹 Medical Imaging & Reporting

• Work with DICOM metadata, radiology reports, and non-DICOM clinical documents

• Assist in developing AI-assisted structured reporting templates (SR / FHIR-aligned)

• Build GenAI features that work alongside 2D/3D viewers and enterprise imaging platforms

🔹 Engineering & Integration

• Develop APIs using Python / FastAPI

• Integrate GenAI services with backend systems (RIS / PACS / VNA / Enterprise Viewer)

• Work with vector databases (FAISS / Pinecone / Chroma) for semantic search

• Participate in model evaluation, hallucination control, and clinical safety checks

🔹 Research & Innovation

• Evaluate latest research in medical GenAI, multimodal AI, and healthcare LLMs

• Prototype new AI workflows for:

  • Blind reads

  • AI second opinions

  • Quality & consistency checks in reports

Eligibility

Final-year students or recent graduates in
Computer Science / AI / Data Science / Biomedical Engineering / Health Informatics

Technical Skills (Expected)

Must Have

• Strong Python fundamentals

• Hands-on experience with LLMs (OpenAI, Azure OpenAI, Gemini, LLaMA, etc.)

• Understanding of prompt engineering and RAG

• Basic API development experience (REST / FastAPI)

Good to Have

• Familiarity with medical imaging concepts (DICOM, modalities, studies, series)

• Experience with LangChain / LlamaIndex / Semantic Kernel

• Knowledge of FHIR / HL7 / Clinical terminologies

• Exposure to Docker, cloud (GCP/AWS/Azure)

Domain Knowledge (Nice to Have)

• Radiology workflows (ordering → acquisition → reporting → distribution)

• RIS / PACS / VNA ecosystems

• Clinical report structuring and terminology (Impression, Findings, Conclusion)

What You’ll Learn

• Real-world GenAI deployment in regulated healthcare environments

• How to build safe, explainable, and scalable AI for clinical use

• End-to-end AI product development—from prototype to production

• Working with imaging data, reports, and enterprise healthcare systems

What We’re Looking For

• Curious, self-driven problem solvers

• Passion for AI + healthcare impact

• Ability to convert ambiguous clinical problems into structured AI solutions

• Strong communication and documentation skills

What We Offer

• Hands-on exposure to production healthcare AI systems

• Mentorship from industry experts in medical imaging & AI

• Opportunity for Pre-Placement Offer (PPO)

• Certificate & recommendation letter upon successful completion