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Open nowPosted 178 days ago

实习-AI平台软件研发工程师

nio/campus867 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now实习-AI平台软件研发工程师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. nio/campus postings stay open a median of 1 days.

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 178 days ago

nio/campus median: 1 days open

The posting

关于 NIO Skyworks NIO Skyworks 是蔚来汽车的企业 AI 平台，致力于构建从基础能力到终端应用的完整 AI 技术栈。我们的产品矩阵包括： - ModelSight: MaaS 模型平台，支持多模型接入和推理优化DataSight: OneLake 大数据平台，包含 Agentic BI 和语义层 - KnowledgeSight: 统一知识平台，整合 Ontology、知识图谱、向量检索 - AgentSight: Agent 搭建平台，支持零/低/高代码开发 - AgentsMarket/SkillHub/McpHub: 企业能力市场化生态 - NIOChat/NIOClaw: 企业级 Super Agent 应用我们目标是成为企业 AI 操作系统，让每个员工都拥有 AI 超能力。岗位职责 1. 核心平台开发 (50%) - 参与 AgentSight、KnowledgeSight、DataSight、ModelSight 等核心产品的后端开发 - 开发 Agent 编排引擎，支持零/低/高代码的 Agent 搭建 - 开发 Ontology 建模工具和统一语义层，实现知识和数据的融合 - 开发联邦查询引擎，支持跨数据源（结构化数据、知识图谱、向量库）的统一查询 - 参与 AgentsMarket/SkillHub 的开发，构建企业能力市场化生态 2. 系统架构与优化 (25%) - 参与微服务架构设计，保证系统的高可用和高性能 - 优化大规模知识图谱的查询性能（支持 2300+节点，45000+边） - 开发分布式任务调度系统，支持 Agent 的并发执行 - 参与系统监控和可观测性建设（Langfuse 集成） 3. 技术创新与研究 (15%) - 跟踪 AI Agent、知识图谱、语义层等前沿技术 - 参与技术预研，探索新技术在 Skyworks 中的应用 - 参与开源社区，贡献代码和最佳实践 4. 协作与文档 (10%) - 与产品、算法、前端团队协作，推动功能落地 - 编写技术文档和 API 文档 - 参与 Code Review，保证代码质量

基础要求： - 2027 届本科及以上学历，计算机、软件工程等相关专业 - 扎实的编程基础，熟练掌握 Python 或 Java/Go 中的至少一种 - 熟悉常用数据结构和算法，有良好的代码规范 - 了解数据库（MySQL/PostgreSQL）和缓存（Redis）的基本使用 - 了解 RESTful API 设计和微服务架构 - 实习期每周至少 4 天，可连续实习 6 个月及以上 加分项： - 熟悉 LangChain、LlamaIndex 等 AI Agent 框架 - 了解知识图谱（Neo4j/JanusGraph）或向量数据库（Milvus/Qdrant） - 有分布式系统、消息队列（Kafka/RabbitMQ）的使用经验 - 熟悉 Docker、Kubernetes 等容器技术 - 有开源项目贡献或技术博客 - 参加过 ACM/ICPC、Kaggle 等竞赛 技术栈（不要求全部掌握，但需要快速学习）: - 后端： Python(FastAPI/Django) / Java(Spring Boot) / Go - 数据库： PostgreSQL, MySQL, Redis - 图数据库： Neo4j, JanusGraph - 向量数据库： Milvus, Qdrant, Weaviate - 消息队列： Kafka, RabbitMQ - 容器化： Docker, Kubernetes - AI 框架： LangChain, LlamaIndex, LangGraph - 监控： Prometheus, Grafana, Langfuse 我们看重的特质： - 技术热情： 对新技术保持好奇，愿意深入研究 - 工程能力： 不仅能写代码，更能写出高质量、可维护的代码 - 系统思维： 能够从架构层面思考问题 - 快速学习： 能够快速掌握新技术和业务领域 - 团队协作： 良好的沟通能力，愿意分享和帮助他人 你将获得 技术成长： - 参与构建企业级 AI 平台的完整技术栈 - 深入学习 Agent 编排、知识图谱、语义层等前沿技术 - 接触大规模分布式系统的设计和优化 - 与顶尖工程师和架构师深度协作 项目经历： - 负责核心模块的开发和优化（可写入简历的亮点项目） - 参与从需求到上线的完整开发流程 - 代码将服务于数千名 NIO 员工 转正机会： - 表现优秀者可获得校招绿色通道 - 提前锁定 NIO AI 平台核心研发岗位 - 成为企业 AI 领域的技术专家 工作场景示例 场景 1: 开发 Agent 编排引擎 - 设计 Agent 的执行流程（任务分解、并行执行、结果聚合） - 实现 Agent 对多种知识源的挂载和查询 - 开发 Agent 的可视化配置界面的后端 API - 优化 Agent 的执行性能，支持高并发 场景 2: 开发统一语义层 - 设计 Ontology 的存储结构和查询接口 - 实现 Ontology 到物理数据源的映射引擎 - 开发联邦查询引擎，支持跨数据源的统一查询 - 实现 Ontology 的版本管理和影响分析 场景 3: 优化知识图谱查询性能 - 分析供应链知识图谱的查询瓶颈 - 设计图索引和缓存策略 - 优化 Cypher 查询语句 - 实现查询结果的分页和流式返回 NIO Skyworks 2027届实习生招聘JD

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