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Open nowPosted 72 days ago

高级存储研发专家（AI 训练数据缓存加速方向）

li/referral788 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now高级存储研发专家（AI 训练数据缓存加速方向）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.

12.1% 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. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 72 days ago

li/referral median: 1 days open

The posting

1.主导设计和研发下一代分布式多级分层缓存加速系统，基于 GPU 主机本地内存、NVMe SSD、远端并行文件系统构建大容量弹性扩缩容的多级缓存架构，实现数据按需与透明加速；​ 2.参与设计和研发百 PB 规模的分布式文件缓存系统，支撑自动驾驶、大语言模型等业务的大规模分布式 AI 训练集群；​ 3.设计并实现智能数据放置与生命周期管理策略（如基于访问热度的分层调度、TTL/LRU 淘汰、预取优化），降低 GPU 因存储 I/O 导致的停顿；​ 4.参与研究和落地高性能存储软硬件技术栈，如 GPU Direct Storage、NVMe-oF、RDMA、Burst Buffer 等，持续优化端到端数据通路性能；​ 5.参与元数据管理系统设计，实现高效的路径查找和缓存机制，保证元数据访问延迟在毫秒级。

1.本科及以上学历，5 年以上分布式存储系统、缓存系统、文件系统或相关大规模系统软件研发经验；​ 2.熟练掌握 Rust、C/C++、Golang 中至少一种系统编程语言，具备在大型软件项目中应用AI Coding 的经验；​ 3.深入理解分布式系统设计原理（一致性、复制、分片、容错），有 Curvine、Alluxio、JuiceFS、Mooncake 等系统研发经验者优先；​ 4.熟悉 Linux 内核存储栈或具备用户态文件系统开发经验；​ 5.了解 AI 训练数据流（PyTorch DataLoader/Dataset、流式数据加载）或推理引擎（vLLM、SGLang）工作原理者优先；​ 6.有强烈的技术好奇心，关注业界前沿技术，具备从论文/开源项目快速落地的能力。

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