Responsibilities: -Optimize the pipeline and model performance of large language models (LLMs) in retrieval-augmented generation (RAG) scenarios -Explore and develop advanced applications of LLMs in multi-modal tasks, function calling, and interactive search -Track the latest advancements in evaluation capabilities of large language models in RAG, multi-modal agents, and function calling, and build systematic evaluation capabilities -Optimize foundational abilities of LLMs (e.g., instruction following, reasoning and planning, long-text memory, and knowledge inheritance) and promote their practical implementation
Qualifications: -Bachelor’s degree or higher in Computer Science or related fields -Background in NLP/search/advertising/recommendation system development, familiar with modern NLP model architectures such as Transformers/BERT -Excellent coding skills, proficient in programming languages such as Python & Shell -Excellent communication and logical expression skills, a passion...