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Open nowPosted 37 hours ago

AI Infra 存储研发工程师 / 专家（多方向、多 HC）

vrfi1sk8a0/index201 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen nowAI Infra 存储研发工程师 / 专家（多方向、多 HC）vrfi1sk8a0/index · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. vrfi1sk8a0/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 37 hours ago

vrfi1sk8a0/index median: 1 days open

The posting

岗位说明 这是一个面向 AI 存储基础设施的岗位族，团队将围绕不同技术方向持续招聘多个 HC，岗位级别覆盖资深工程师到技术专家。 你不需要覆盖全部存储技术栈，只需在一个或多个方向具备深入经验，我们会根据你的技术专长匹配具体岗位和团队。

岗位定位 我们正在建设面向自建智算集群的下一代 AI 存储基础设施，推动云上存储能力向自建 IDC 和 GPU 集群下沉，打造基于 RDMA、NVMe 和全闪介质的高性能分布式存储系统。 系统将服务大模型训练 Checkpoint、海量训练数据、Dataloader 数据读取及 KV Cache 等核心场景，重点解决大规模 AI 业务中的吞吐、时延、可靠性和成本问题。

重点技术方向 - 存储下云与智算基础设施：将云上文件、对象、块存储能力迁移和重构到自建智算集群，建设面向 AI 业务的存储平台。 - RDMA 高性能存储：围绕 RoCE / InfiniBand、NVMe-oF、SPDK、io_uring、零拷贝和异步 IO，优化端到端数据访问链路。 - 全闪分布式存储：负责客户端、元数据、存储引擎、分片、副本、纠删码和数据保护等模块。 - AI 场景性能优化：优化 Checkpoint 保存与恢复、训练数据读取、KV Cache 访问，提升 GPU 利用率和集群整体效率。 - 稳定性与可观测性：建设故障注入、性能分析、链路观测、故障恢复和数据修复能力。

你将负责 1. 参与存储下云整体架构设计，建设面向自建智算集群的高性能存储系统。 2. 研发基于 RDMA/NVMe 的高吞吐、低延迟数据访问链路。 3. 负责客户端、元数据服务、存储引擎或数据保护等核心模块。 4. 解决大模型训练和推理场景中的 Checkpoint、训练数据及 KV Cache 存储问题。 5. 持续优化系统吞吐、IOPS、尾延迟、CPU 开销、GPU 利用率和存储成本。

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