岗位描述
岗位职责：
优化大语言模型（LLMs）在检索增强生成（RAG）场景下的系统流程与模型性能。
探索并开发大语言模型在多模态任务、函数调用和交互式搜索等方向的先进应用。
跟踪大语言模型在 RAG、多模态智能体与函数调用等方面的最新评测进展，构建系统化的评估能力体系。
优化大语言模型的基础能力（如指令理解与遵循、推理与规划、长文本记忆、知识迁移与继承等），并推动其在实际业务中的落地应用。
任职要求：
计算机科学或相关专业本科及以上学历。
具备 NLP / 搜索 / 广告 / 推荐系统开发背景，熟悉 Transformers、BERT 等现代 NLP 模型架构。
具备优秀的编码能力，熟练使用 Python、Shell 等编程语言。
具备良好的沟通能力与逻辑表达能力，热爱探索式学习，具备良好的团队合作精神和强烈的责任心。
加分项：有具有影响力的成果（如顶级学术会议论文、优质开源项目贡献等）。
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 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).