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Open nowPosted 231 days ago

高级搜索与 RAG 算法工程师

c0fu1j3a9m0/referral33 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now高级搜索与 RAG 算法工程师c0fu1j3a9m0/referral · Shanghai, Chinese Mainland

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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. c0fu1j3a9m0/referral postings stay open a median of 1 days.

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. 58.1%60 days
This job: posted 231 days ago

c0fu1j3a9m0/referral median: 1 days open

The posting

1. 负责科研文献搜索系统的算法设计与优化，包括关键词检索、向量检索、混合召回、多路召回、排序与重排序等能力建设。 2. 负责 RAG 检索增强链路建设，包括 Query Rewrite、意图理解、文档召回、证据检索、上下文构造、答案溯源和结果评估等。 3. 负责 Embedding、Reranker 等模型的选型、评测、优化和落地，提升科研文献、数据集、方法、实验指标等内容的语义匹配效果。 4. 参与论文图谱、引用图谱、主题图谱、方法图谱、数据集图谱等科研知识图谱建设，支持论文关系发现和科研脉络分析。 5. 建设搜索与 RAG 系统的评测体系，包括离线评测、bad case 分析、LLM-as-a-Judge、指标监控和持续优化闭环。 6. 与产品、后端、数据平台、模型团队协作，推动搜索、RAG、图谱和模型能力在实际业务中稳定落地。

1. 计算机、人工智能、信息检索、自然语言处理、数据挖掘、知识图谱等相关专业本科及以上学历。 2. 具备搜索引擎、推荐系统、广告排序、知识图谱、学术搜索、RAG 系统等相关项目经验，至少深入参与过其中一个方向的核心算法或系统建设。 3. 熟悉搜索系统核心技术，包括倒排索引、BM25、向量检索、ANN、Embedding、Rerank、多路召回、排序模型等。 4. 熟悉搜索排序或推荐排序相关方法，具备召回、粗排、精排、重排、特征工程、相关性优化、效果评估等实际经验。 5. 具备 LLM 应用经验，熟悉 RAG、Agentic Retrieval、Query Rewrite、LLM-as-a-Judge、答案溯源、证据链构建等方向。 6. 具备深度学习模型训练、微调或评测经验，熟悉 PyTorch、Transformers、Sentence-Transformers、BGE、Qwen Embedding / Reranker 等模型或相关技术栈。 7. 熟悉知识图谱或图计算相关技术，包括实体建模、关系建模、图存储、图遍历、相似节点发现、路径分析等。 8. 熟练使用 Python / Java / Scala / Go 中至少一种语言，具备良好的算法实现能力、工程落地能力和问题排查能力。 9. 具备较强的数据分析能力，能够基于日志、样本、指标和 bad case 分析问题，并推动算法持续迭代。 10. 具备良好的沟通协作能力，能够与产品、后端、数据平台、模型团队共同推进复杂系统落地。

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