工作职责:

-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

任职要求:

-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 for exploratory learning, a good team collaboration attitude, and a strong sense of responsibility
-Preferred: impactful work (e.g., publications in academic conferences, open-source contributions)