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Open nowPosted 86 days ago

异构算力研发工程师 - AI算力基础设施

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now异构算力研发工程师 - 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 23 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: 23 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。

1、实例研发与交付：参与异构云服务器实例（GPU、NPU云服务器、裸金属、HPC集群等）的方案设计、开发上线与交付；理解前沿AI业务场景需求，结合火山引擎云基础设施底座及GPU、NPU、CPU、RDMA网卡等硬件特点完成实例研发以及持续的竞争力构建，支撑大模型训练、推理、AI Agent等AI业务的算力需求； 2、稳定性架构与能力建设：参与异构云服务器的稳定性架构设计与全链路稳定性能力建设；深入理解GPU、NPU、CPU、RDMA网卡等硬件特点及Linux Kernel等系统软件架构，从底层硬件适配到上层软件栈的稳定性保障方案落地，重点面向大模型训练、推理等业务场景，构建异构实例监控、告警、诊断、巡检、自愈等稳定性体系，实现潜在风险的提前识别与自动化处置，持续提升实例运维的效率与质量； 3、异构算力供给与资源效率：参与异构算力资源供给侧的平台化与智能化建设，保障内外部算力流转的效率与成功率；负责异构资源池的备机管理、碎卡治理、资源画像与潮汐复用策略建设，推动字节跳动内部业务与外部客户的资源高效流转，最大化资源利用率，降低算力使用成本； 4、AI业务场景支持与算力适配：深入理解内外部AI业务场景的算力诉求，从实例层面对接业务需求并给出技术方案；构建典型AI业务场景的算力画像，沉淀场景化实例模板与最佳实践；针对大模型训练、推理、智驾、AIGC、搜广推等场景，开展异构实例与业务框架、分布式策略的兼容性验证与性能摸底；推动业务侧算力问题的端到端闭环，联动底层架构团队解决跨层技术问题，保障业务高效落地； 5、AI与智能化工具研发：参与异构计算垂类Agent与智能化工具的研发，探索AI模式在实例研发、稳定性运维、资源运营等场景的落地；将团队领域知识沉淀为可复用的智能能力，持续提升团队工程效能与业务响应速度。

1、2027届获得本科及以上学历，计算机、软件工程、电子信息、微电子等相关专业优先； 2、掌握扎实的算法、数据结构、操作系统、计算机网络与计算机体系结构基础，熟练掌握C/C++、Python、Go中至少一种编程语言； 3、对以下方向中的一个或多个具备背景知识或研究兴趣：GPU/NPU/RDMA网卡硬件与驱动、高性能网络（RDMA/NVLink/IB）、虚拟化技术（KVM/QEMU）、云计算管控平台、Linux Kernel； 4、具备良好的沟通协调能力、学习能力与责任心，乐于团队协作，能够积极配合完成分配的任务。

加分项 1、具备GPU/NPU/CPU、RDMA相关性能分析、故障排查及监控工具的开发或使用经验，熟悉Linux系统常用调试工具与方法； 2、对AI训练/推理任务的运行方式、系统级挑战有基本认知，有GPU驱动、CUDA环境、集合通信库（NCCL/HCCL）的部署、配置或排障经验； 3、有大模型训练/推理任务在多机多卡集群上的部署、兼容性验证或性能摸底经历； 4、有LLM应用开发、AI Agent或AI工具相关的项目经验，对用AI提升工程效能有实践和思考； 5、熟悉QEMU、KVM、vfio、SR-IOV等虚拟化/直通技术，或Kubernetes/容器技术，有相关开发或使用经验； 6、关注国产AI加速卡与自研芯片的生态发展，有相关调研或实验经验；有异构计算、AI Infra方向的顶会/期刊论文、开源贡献或高质量博客产出。

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