R&D Engineer - Expert

1. Enhance R&D efficiency through AI technology application and implementation 2. AI Application Development and Project Delivery Lead AI project requirements analysis, technical solution design, and product delivery Complete fine-tuning, alignment, and inference optimization for general models, embedded models, and inference models Build efficient and usable Prompt Engineering workflows to improve model task performance 3.

Multi-Agent Systems and Framework Applications Implement multi-agent workflow orchestration using frameworks like LangChain, LangGraph, and MCP Design and implement key reasoning paradigms (ReAct, CoT, ToT) to improve agent system responsiveness and controllability Understand agent platforms such as Coze, FastGPT, and Dify 4. Knowledge Retrieval and RAG Systems Build document knowledge retrieval systems based on vector databases (Milvus, FAISS, Chroma, etc.) Design RAG architecture solutions to enable context-enhanced interactions with large language models (e.g., ChatGPT, DeepSeek) Improve document recall quality and reasoning relevance 5.

Technical Research and Capability Development Track AI technology trends (model alignment, multimodality, multi-agent systems, etc.), regularly complete technical research, develop application prototypes, or deliver technical presentations