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Open nowPosted 86 days ago

面向AIDC的下一代高密度数据中心基础设施创新与AI智能运维研究 - AI算力基础设施

ByteDance19,261 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now面向AIDC的下一代高密度数据中心基础设施创新与AI智能运维研究 - AI算力基础设施ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.4% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 27 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 86 days ago

ByteDance median: 27 days open

The posting

团队介绍：字节跳动基础设施部门，负责字节跳动的全栈算力基础设施，从芯片服务器产研、到超大规模数据中心，到传统云平台和如今的AI Native Cloud，全方位为抖音、豆包、今日头条、飞书、火山引擎等各类产品提供领先、稳定的百万量级大规模算力基础设施服务。我们的领域涵盖数据中心建设、内核操作系统开发、服务器集群管理、高速网络通信、EB级数据存储体系、搜索型数据库探索、基于LLM的AI基础设施的研发调度与治理等，致力于打造业界领先的、面向LLM的AI云原生基础设施架构与产品矩阵。

课题介绍： 随着智能计算与AIDC产业快速发展，数据中心单机柜功率密度持续攀升，传统基础设施在换热效率、节水效果、能源利用方面存在短板，同时海量运维数据未充分利用，运维效率依赖人工经验，难以适配产业高质量发展与政策要求。 本课题从技术创新与智能化赋能两方面开展研究：一方面围绕液冷技术、节水无水冷源、供配电储能方向协同创新，突破现有技术瓶颈，适配高密度功率需求与双碳、节水政策要求；另一方面构建数据中心运维AI Agent体系，利用大模型技术从海量多模态异构运维数据中学习，实现多Agent协作完成从监控、诊断到修复的全流程自动化，打造PUE智能优化闭环，支撑从"被动响应"到"主动预测与自愈"的范式转变。通过硬件技术创新与AI智能化运维深度结合，全面提升数据中心能效、可靠性与运维效率。

课题挑战： 1、多技术协同创新：液冷技术需突破高效换热与系统可靠性，节水冷源需实现低WET与干湿协同，供配电储能需解决源网荷储适配与全链路效率提升，多方向协同创新难度大； 2、多Agent协作体系设计：需构建面向复杂运维流程的多Agent协作框架，实现从监控、诊断到自动修复的端到端自主执行，技术整合难度高； 3、PUE智能优化闭环构建：需要基于时序预测与强化学习实现暖通与电力系统智能控制，达到超越人类专家的优化效果，对算法与工程落地要求高； 4、异构数据根因归纳：需要利用大模型从海量异构监控数据中自动完成故障根因分析与知识沉淀，对模型理解与泛化能力要求高； 5、技术落地适配：硬件创新需要兼顾政策合规与行业适配，AI运维需要对接现有平台工具，二者融合落地挑战大。

课题价值： 1、突破数据中心核心技术瓶颈，增强技术竞争力； 2、实现节水低碳运行，通过AI智能运维保障数据中心合规、高效、稳定长效运营。

1、2027届毕业，获得博士学位，计算机、自动化、电气、能源等相关专业优先； 2、熟悉LLM原理与技术生态，有大模型应用或多模态内容理解的工程经验者优先； 3、深刻理解AI Agent设计思想，有从0到1独立开发Agent应用的经验者优先； 4、具备优秀的问题抽象能力与落地驱动力，善于将研究成果转化为实际生产力。

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