shijiezheng

Focused on applying LLMs to audio and content platforms, improving intelligent recommendation systems and chatbot interactions. Developed a context-aware dialogue assistant tailored for audio platform users, optimizing personalization and content delivery. Participated in prompt engineering and fine-tuning tasks for internal knowledge-based AI tools. Collaborated with product teams to align AI solutions with business needs, supporting product enhancement through data-driven iteration. Explored integration of memory modules and persona frameworks to enhance long-form conversation quality.

Assisted in building AI tools and systems for enterprise-scale applications, contributing to backend services and model inference pipelines. Focused on practical deployment of LLM-powered solutions, emphasizing performance optimization, reliability, and scalability. Conducted technical evaluations, bug fixes, and documentation for production-ready AI tools used in internal operations. Collaborated with senior developers to refine workflow automation and implement feature updates based on stakeholder feedback. Gained hands-on experience in international work culture, DevOps practices, and Agile team collaboration.

Participated in the development and deployment of AI applications using large language models (LLMs), focusing on prompt engineering, retrieval-augmented generation (RAG), and multi-turn dialogue optimization. Designed and built intelligent chatbots and internal tools to enhance business productivity, including an LLM-powered memory system for AI NPCs. Published an SCI paper titled MemoryRepository for AI NPC, presenting a modular memory architecture for long-term interactions in conversational agents. Contributed to model fine-tuning and custom dataset preparation, improving chatbot coherence, retrieval accuracy, and human-like interaction quality. Worked cross-functionally with product and engineering teams to integrate LLM solutions into real business workflows.