GE Healthcare Recruitment 2025 | Internship | Apply Now!

• We are looking for a passionate and highly motivated individual, who has some knowledge on Large Language Models (LLMs)/ Transformers/ GenAI/ Agentic AI, to join our MICT team at GE Healthcare, to do internship.
• 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.
• 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.
• Ensure high accuracy and reliability of model outputs with possible auto-validation, minimizing hallucinations and manual revalidation, involving large- scale datasets.
• Implement robust data preprocessing pipelines to clean, normalize, and structure service record data. • 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 to enhance model responses using historical records and technical documentation.
• Collaborate with domain experts to validate model outputs and incorporate feedback for continuous improvement.
• Explore and execute model training strategies and agent introduction if pre-trained LLMs do not meet performance expectations.
• Work with cloud platforms and tools (e.g., AWS) and leverage Python for model development and deployment.

Skills:

• Understanding of large-scale AI such as generative AI models, large vision/language models, and Agentic AI models.
• Strong proficiency in Python, C++ and AI/ML frameworks.
• Experience with prompt engineering, RAG-based architectures and frameworks such as Vector databases.
• Familiarity with medical products and related service data and RCA methodologies.
• Ability to work with large-scale datasets and build scalable AI solutions.
• Knowledge of cloud infrastructure and deployment practices.
• Prior experience in AI projects is highly desirable; however, the ability to learn quickly and adapt to new challenges is considered essential.

GE Healthcare Off Campus Qualification: 

• Currently pursuing post- graduation (M. Tech or ME) in Computer Science/ AI/ Data sciences from a reputed institute.

GE Healthcare  Selection Process:

• Resume Screening
• Initial Interview
• Technical Assessment
• Panel Interview
• Behavioural Interview
• Final Interview
• Reference Check
• Job Offer

How to Apply for GE Healthcare Off Campus Drive 2025?

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