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Open nowPosted 163 days ago

蔚来AGI超星计划-组织知识协同系统

nio/campus870 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now蔚来AGI超星计划-组织知识协同系统nio/campus · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 163 days ago

The posting

课题介绍 当前，组织内越来越重视优秀实践方法论的沉淀与共享。相比依赖口口相传的经验传递方式，我们希望通过智能化技术，更高效地整理、归纳和复用优秀团队成员在真实业务场景中的工作方法与协作经验，帮助团队提升知识传承效率与协同能力。 本课题旨在探索一种“组织知识协同”的产品与技术方案。 在用户授权与数据合规的前提下，围绕真实业务场景中的经验内容，系统化整理问题分析路径、沟通方式、决策参考依据以及执行流程，形成可辅助学习、协作与业务支持的智能化工具。 该系统的目标并非替代个人，而是帮助团队更高效地共享优秀实践经验，提升新人学习效率，增强跨团队协作能力，并促进组织知识的长期沉淀与持续演进。 重点研究方向包括： - 如何结构化整理业务经验与工作方法； - 如何提升系统对优秀实践经验的理解与辅助能力； - 如何建立真实业务场景下的效果评估机制； - 如何设计安全边界，保障用户授权、隐私安全与合理使用。 预期产出 1. 一个可演示的“组织知识协同”产品原型 - 具备清晰的产品形态与交互流程； - 能够围绕真实业务场景，对优秀实践经验进行结构化整理与智能化辅助； - 支持知识检索、经验学习、业务问答与协作支持等能力； - 可在试点场景中完成真实业务验证，并通过用户反馈、任务完成质量等方式评估实际效果。 2. 一套可复用的业务经验整理与知识协同方法论 - 覆盖从经验拆解、数据整理、模型对齐到效果评估的完整链路； - 形成标准化的知识整理框架、操作流程与安全规范； - 支持在不同业务场景中探索应用，提升组织知识共享与协同效率； - 为组织知识沉淀、人才培养与跨团队协作提供长期支持

  • 精通深度学习原理，对Transformer、大语言模型有扎实的理论基础和实践经验；
  • 强大的系统性思维与问题定义能力；
  • 精通并有主流大模型的相关训练和使用工作经验，深入了解主流Agent框架和应用；
  • （加分）在国内外顶尖实验室或者模型团队经历；
  • （加分）重度使用claude、cursor、codex等相关AI工具开发者优先；
  • 学历：硕士及以上在读；
  • 实习时长：6个月以上。
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