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Open nowPosted 6 hours agoWe saw it 60 min after it went up

云平台研发工程师（GPU 集群与存储方向）

agirobot/socialrecruitment484 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now云平台研发工程师（GPU 集群与存储方向）agirobot/socialrecruitment · Shanghai, 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 agirobot/socialrecruitment's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. agirobot/socialrecruitment postings stay open a median of 6 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 6 hours ago

agirobot/socialrecruitment median: 6 days open

The posting

岗位职责 1. 负责平台 GPU 计算资源的接入与管理，对接云厂商及自建服务器，建设统一的节点注册、资源发现、健康检查和使用状态管理能力，支持不同来源计算资源的统一使用。 2. 建设训练、评测、数据处理及模型转换任务的资源分配与执行能力，完善队列、GPU 分配、资源配额、并发限制和故障恢复机制，提升多节点、多 GPU 场景下的利用率与运行稳定性。 3. 负责 GPU 节点及其与平台之间的通信链路，完善节点 Agent、心跳、任务下发、状态回传、日志采集及异常重连机制，排查网络、权限、容器环境和节点失联等问题。 4. 负责 S3 兼容对象存储、阿里云 OSS、本地及共享存储的接入与管理，建设统一存储访问能力，完善授权、生命周期、容量监控、备份恢复及成本管理。 5. 优化机器人端、平台、对象存储与 GPU 节点之间的数据传输，支持大文件及海量小文件上传下载、分片传输、断点续传、完整性校验、限流与失败重试，结合缓存、预取和内网链路降低任务准备时间及传输成本。 6. 建设容器镜像、运行环境和基础设施自动化能力，完善 GPU 驱动、CUDA、容器运行时及依赖兼容管理，支持节点初始化、环境自检、批量部署、升级和回滚。 7. 建设计算、存储与网络的监控告警体系，持续分析 GPU 利用率、显存、磁盘 I/O、带宽及任务排队情况，定位容量与性能瓶颈，开展资源规划和成本优化。 8. 参与客户私有化与离线交付，完成云资源、GPU 服务器、网络和存储方案设计及部署验证；对接云厂商和客户 IT，推进资源开通、网络连通、故障处理及运维移交。

任职要求 1. 计算机或相关专业本科及以上学历，有云平台、基础设施、GPU 集群或 DevOps 相关研发与运维经验。 2. 熟悉 Go 或 Python，能够开发资源管理服务、节点 Agent、云 API 对接及自动化工具，具备良好的工程实现和排障能力。 3. 熟悉 Linux、Docker / containerd 和 Kubernetes，理解容器网络、持久化存储、资源配额及 GPU 资源管理，有多节点环境部署或维护经验。 4. 熟悉 NVIDIA GPU、驱动、CUDA 和 GPU 容器环境，能够排查 GPU 不可见、显存不足、驱动兼容及资源占用等问题，理解训练与推理对计算、存储和带宽的需求。 5. 熟悉阿里云或其他主流云平台的计算、网络、存储及权限体系，能够通过 API / SDK 接入资源，处理 VPC、路由、安全组、内外网访问及跨环境连通问题。 6. 熟悉 S3 / OSS / MinIO 等对象存储中的一种或多种，理解分片上传、重试、校验、访问授权和生命周期管理；具备传输吞吐分析及存储容量管理经验。 7. 熟悉 TCP/IP、DNS、HTTP / HTTPS、TLS 及反向代理，能够定位数据传输中的网络、磁盘、并发和服务端限流等瓶颈。 8. 具备监控告警、日志分析、发布回滚及故障恢复实践，能够协同研发、云厂商及客户 IT 解决跨系统问题，并适应客户现场和离线部署场景。

加分项 - 有 GPU 集群、AI 训练推理平台或混合云资源管理经验。 - 熟悉 Kubernetes Device Plugin、Volcano、Kueue、Ray 等资源管理或任务调度组件。 - 有模型与数据集缓存、共享文件系统、跨地域传输或大规模对象存储优化经验。 - 熟悉 Terraform、Ansible、Helm、Prometheus、Grafana、DCGM 等工具，有基础设施自动化及 GPU 监控实践。

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