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...