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Open nowPosted 130 days ago

知识图谱工程师/专家

anker-in/experiencedhireen167 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now知识图谱工程师/专家anker-in/experiencedhireen · Shenzhen, Guangdong, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

12.3% 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. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 130 days ago

The posting

岗位职责： 1、知识资产构建：主导质量知识库的结构化建设，将质量手册、程序文件、失效案例、检验标准转化为 AI 可检索的结构化知识；目标：知识图谱覆盖≥3 个质量域，RAG 召回准确率≥85%； 2、知识图谱开发（核心产出）：构建质量失效模式知识图谱，设计本体模型，整合历史案例、原因分析、改进措施，支持智能匹配与跨品类经验复用； 3、规则工程化：与质量专家协作，通过结构化访谈提取专家隐性知识，将专业判断抽象为可执行规则（含触发条件/判断标准/处置路径），为 AI Agent 工具建设提供标准化输入； 4、知识质量管控：建立知识库内容的评审机制、更新规则，确保知识库持续处于高质量可用状态。 岗位要求： 1、学历：硕士及以上，计算机科学、信息管理、人工智能或相关专业； 2、知识图谱/知识工程背景必要条件：有知识图谱建设、本体设计、知识建模或知识结构化相关实践经验；熟悉图数据库（Neo4j/NebulaGraph 等）；有 RAG 系统设计或 LLM 知识增强应用经验者优先； 3、AI 工具理解：深度理解 LLM 的能力边界和知识检索（RAG）原理；有 Prompt 工程实践经验；能评估知识库对 AI 推理质量的影响； 4、质量/工程领域经验加分项：有制造、质量、工业或医疗等实体领域知识工程经验者优先；纯技术背景无行业经验者可通过入职后与质量专家搭档补足； 5、沟通提炼能力：善于向领域专家提问和提炼，能将复杂专业经验转化为结构清晰的规则和知识条目；具备跨专业协作和项目推动能力。

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