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Open nowPosted 140 days ago

AI 平台高级 SRE 工程师 / DevOps 工程师

li/referral787 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowAI 平台高级 SRE 工程师 / DevOps 工程师li/referral · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on li/referral's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

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

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%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 140 days ago

li/referral median: 1 days open

The posting

1. 负责理想汽车 AI 平台大规模 GPU 集群、RDMA 网络及并行高速存储的稳定运行与日常运维，保障训练、推理等核心 AI 业务高效交付。 2. 负责大规模 GPU 集群在训练任务、资源调度、网络通信、存储访问等场景下的故障定位与问题解决，持续提升平台稳定性和可用性。 3. 深入理解 AI 训练与推理业务场景，参与 AI 平台在 Kubernetes 多集群、监控告警、日志检索、故障诊断等方向的云原生架构演进与落地。 4. 建设和完善 AI 平台运维体系，包括稳定性治理、故障应急、容量管理、资源运营、SLA 保障等，提升平台规模化运维能力。 5. 推动运维自动化和智能化建设，开发自动化运维工具、巡检工具、故障自愈能力和运维 Agent，降低人工干预成本，提升问题发现与处理效率。

1. 具备较强的问题分析和解决能力，能够在复杂系统环境下快速定位问题；具备良好的沟通能力、责任心和团队协作精神。 2. 熟悉 Linux 操作系统、Shell 脚本、网络基础知识，具备扎实的系统排障能力；至少熟练掌握一门编程语言，Golang 优先。 3. 熟悉 Kubernetes、containerd、Istio、NVIDIA Device Plugin 等云原生技术，具备生产环境落地或运维经验。 4. 熟悉服务器硬件、GPU、RDMA 网络、并行存储等 AI 基础设施，能够处理 GPU 故障、网络故障、存储故障及集群稳定性问题。 5. 了解 PyTorch 分布式训练、NCCL、GPU 通信等基本原理，具备常见训练故障排查经验者优先。 6. 熟悉 Prometheus、Loki、Grafana 等监控与日志体系，能够建设指标、告警、日志检索和故障定位能力。 7. 有自动化运维工具、故障巡检工具、运维 Agent 或平台化运维系统建设经验，能够通过工具化手段提升运维效率和故障自愈率。

加分项 1. 有千卡级 GPU 集群、RDMA 网络、并行存储集群运维经验者优先。 2. 熟悉 Kubernetes、Istio、Karmada、Prometheus、Loki、Grafana 等云原生和可观测性项目者优先。 3. 有阿里云、火山云等公有云平台使用、运维或混合云管理经验者优先。 4. 有 AI 训练平台、推理平台、MLOps 平台、机器学习基础设施相关经验者优先。 5. 有大规模集群稳定性治理、资源治理、故障自愈、容量运营经验者优先。

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