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(#8242335002) 2026 Intern, Gen AI/LLM Research

Samsung Research America
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Lab Summary: We are an interdisciplinary team with an aim to empower providers, consumers, and clinical researchers. We develop GenAI/LLM-based Health AI technologies for Samsung Health, explore use cases by co-innovating with our partners, and design services through pilots that eventually turn into groundbreaking commercial, consumer-grade products that are used every day. Our work has been internationally recognized with 70+ peer-reviewed publications and 10 design awards.

Position Summary: Samsung Research America Digital Health Team is looking for Ph.D. candidates with solid GenAI/LLM technology background and digital health-related research project experiences in health chatbot, RAG, fine-tuning, evaluation, agentic framework development. Samsung’s unique advantage in consumer electronics market and growing focus on digital health will provide you with unprecedented big data and health analytics challenges.

Position Responsibilities:  

  • You will work with an agile team to innovate and develop disruptive digital health services and solutions
  • Support projects leveraging smart phones, wearables and hearables in health/wellness domain, your work will significantly benefit real-world patients, elderly, physicians and caregivers.

Required Skills:

  • Currently pursuing a Ph.D. in computer science or related areas
  • Hands-on project experience and tangible past deliverables in GenAI/LLM application domain
  • Solid coding skills with prototyping experience in data science and popular machine learning frameworks
  • Strong knowledge in ML/AI, signal processing, deep-learning, generative AI
  • Experience with cloud infra services like Azure, GCP, AWS
  • Good communication/presentation skill and team work spirit
  • Publications in top-tier academic conferences and journals

Special Attributes:

  • Experience in time-series data analytics, recommendation engine, NLP
  • Strong mathematics background, especially statistics
  • Turn the analyzed data into actionable insight and/or understandable visualization
  • LLM-based chatbot development
  • RAG/Fine-tuning of LLM/SLM models
  • Auto-evaluation of LLM in health domain
  • Agentic framework/application development experience