LLM & Physiological Signal AI Development Engineer (BDL)

R&D of AI systems for healthcare and smart care environments, focusing on the development and deployment of applications based on Large Language Models (LLMs), physiological signal analysis, multimodal AI, and generative AI to support clinical decision-making, care services, and interactive RAG (Retrieval-Augmented Generation) systems.
1. Design and optimize prompts and multi-agent task workflows (e.g., ReAct, CoT).
2. Develop medical physiological signal analysis models for applications such as human behavior recognition, AI-assisted interpretation of physiological signals, and analysis of medical device documentation.
3. Build multimodal AI systems: Integrate physiological signals, speech, and text data to develop smart interactive applications (e.g., voice assistants, care robot interfaces).
4. Establish RAG systems and knowledge bases (using Qdrant/Neo4j): Integrate medical databases (e.g., clinical guidelines, SOPs, medical device data) and construct vector and graph databases.

Requirements

1. Collaborate with front-end and back-end engineering teams; experience integrating APIs or working in clinical application environments is a plus.
2. Proficient in Python and LLM frameworks such as LangChain.
3. Experienced in prompt engineering and the implementation of RAG systems.
4. Experience with physiological signal analysis or multimodal AI model development is highly desirable.
5. Familiar with Git and team collaboration workflows.