Intern

GE Healthcare GE Healthcare · Healthcare · Bengaluru, Karnātaka, India · Engineering / Technology

The intern will develop and deploy an AI model for automating root cause analysis (RCA) from historical service record data. This involves processing unstructured complaint text, extracting root causes and resolutions, and potentially fine-tuning LLMs or introducing agents. A RAG framework will be integrated, and the work will leverage cloud platforms and Python.

What you'd actually do

  1. As an intern, you are expected to develop and deploy an AI model to analyse closed service records spanning across various product configurations in Install Base.
  2. Extract and organize critical information such as root causes, resolutions, and relevant keywords to represent the distribution of contributing factors, enabling a comprehensive and holistic analysis.
  3. Ensure high accuracy and reliability of model outputs with possible auto-validation, minimizing hallucinations and manual revalidation, involving large- scale datasets.
  4. Implement robust preprocessing pipelines to clean, normalize, and structure service record data.
  5. Evaluate and fine-tune Large Language Models (LLMs) such as GPT-4o for domain specific RCA tasks.

Skills

Required

  • Python
  • C++
  • AI/ML frameworks
  • prompt engineering
  • RAG-based architectures
  • Vector databases
  • large-scale datasets
  • scalable AI solutions
  • cloud infrastructure
  • deployment practices

Nice to have

  • Large Language Models (LLMs)/ Transformers/ GenAI/ Agentic AI
  • GPT-4o
  • medical products and related service data and RCA methodologies
  • Prior experience in AI projects

What the JD emphasized

  • highly motivated individual
  • Large Language Models (LLMs)/ Transformers/ GenAI/ Agentic AI
  • AI model to analyse closed service records
  • Extract and organize critical information such as root causes, resolutions, and relevant keywords
  • Ensure high accuracy and reliability of model outputs with possible auto-validation, minimizing hallucinations and manual revalidation
  • Evaluate and fine-tune Large Language Models (LLMs) such as GPT-4o for domain specific RCA tasks
  • Retrieval-Augmented Generation (RAG) framework
  • model training strategies and agent introduction
  • Understanding of large-scale AI such as generative AI models, large vision/language models, and Agentic AI models
  • Experience with prompt engineering, RAG-based architectures and frameworks such as Vector databases
  • Familiarity with medical products and related service data and RCA methodologies
  • build scalable AI solutions
  • Prior experience in AI projects is highly desirable

Other signals

  • Develop and deploy an AI model to analyze closed service records
  • Extract and organize critical information such as root causes, resolutions, and relevant keywords
  • Evaluate and fine-tune Large Language Models (LLMs) such as GPT-4o for domain specific RCA tasks
  • Design and integrate a Retrieval-Augmented Generation (RAG) framework
  • Explore and execute model training strategies and agent introduction