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Open nowPosted 6 days ago

AI Infra 平台研发实习生

vrfi1sk8a0/379481107 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAI Infra 平台研发实习生vrfi1sk8a0/379481 · Shanghai, Chinese Mainland

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Early applications get read.

12.4% 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. 12.4%7 days
  4. 20.0%14 days
  5. 35.5%30 days
  6. 58.6%60 days
This job: posted 6 days ago

The posting

团队使命 面向大模型训练与推理，集群资源调度、高性能网络，以及集群与模型的协同设计，是释放算力潜能、提升 AI 基础设施整体效率与稳定性的关键。我们致力于将复杂的底层基础设施转化为高效、可靠、易用的算力服务，让每一份算力得到更充分、更高效的利用。

岗位介绍 本岗位属于集群资源调度与资源管理方向。团队围绕 CPU、GPU、NPU 等异构算力建设资源管理与故障治理平台，连接 CMDB（配置管理数据库）、资源状态、故障流转、维修协作与自动验收，通过软件工程提升资源利用率，减少故障造成的算力损失，为训练推理任务的稳定运行提供支撑。 你将在导师指导下，根据个人基础与项目需求，参与资源管理与后端可靠性、故障治理与 Kubernetes 控制器等方向中的具体模块研发。我们希望你从真实问题出发，经历需求分析、方案设计、编码、测试与交付，逐步具备独立完成模块开发和定位问题的能力。

1. 参与 AI Infra 平台后端研发，完成资源信息建模、查询与状态管理、工单流转、操作审计或系统集成等具体功能，提升资源管理的自动化程度与易用性。 2. 参与故障事件采集、节点健康检查、故障查询及处理流程开发，帮助连接故障信号、资源状态、执行任务与恢复结果，提升故障处理效率。 3. 根据项目方向，参与 Kubernetes Controller/Operator 的功能开发与测试，学习并实践事件处理、状态同步、幂等和失败重试等机制。 4. 编写单元测试、接口测试和自动化工具，利用日志、指标与实验复现定位问题，参与改进代码质量、系统性能和运行可靠性。 5. 参与代码评审、技术文档编写和交付验证，在导师指导下完成有明确边界、可验证结果的研发任务，逐步承担模块维护工作。

1. 预计 2028 年及以后毕业的本科、硕士或博士在读学生，计算机、软件工程、电子信息等相关专业。 2. 具备扎实的数据结构与算法基础，掌握计算机组成与体系结构、操作系统、计算机网络和数据库的基础知识，愿意深入理解程序与系统的运行机制。 3. 熟练掌握 Go、C/C++、Java、Python 等至少一门编程语言，具备独立编码和调试能力，愿意使用 Go 参与平台研发。 4. 熟悉 Linux 基本操作和 Git，能够阅读已有代码、复现问题，并通过测试验证自己的修改；有课程实验、个人项目、实习或开源实践，能清楚说明设计思路、实现过程和遇到的问题。 5. 对 AI 基础设施、资源调度、分布式系统或故障治理有持续兴趣，能够主动分析问题、沟通进展，并对交付结果负责。 加分项 - 有 Go 后端、数据库应用、异步任务、自动化工具或资源管理相关项目经验。 - 了解容器与 Kubernetes，有 Controller/Operator 实践，或使用过 client-go、controller-runtime 等工具。 - 对 GPU、数据中心网络、高性能通信或并行计算有学习与实践经历；能够通过实验分析计算、内存或通信瓶颈。 - 有监控告警、日志分析、故障复现、性能测试或开源贡献经验。 - 在大型开源项目中有深度贡献，或者有优秀的个人开源项目，或是出色且资深的 HomeLab 玩家。 - 完成过 CS61C、MIT 6.004、CMU 15-213、CS149、MIT 6.823/6.824、CSCI 0300 等相关课程的实验或项目，或具备同等实践经验。我们关注你解决过的问题和形成的理解。 你将获得 - 参与服务于大模型训练与推理的真实基础设施项目，理解资源管理、故障治理与算力效率之间的关系。 - 在导师指导和代码评审中积累 Go 后端、云原生与分布式系统工程经验，逐步完成从功能实现到可靠交付的能力进阶。 - 通过有明确产出的模块研发、测试与问题定位，建立系统分析能力，形成可展示、可复盘的工程实践成果。

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