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Open nowPosted 44 days ago

大模型存储科研实习生

sii-czxy/campus170 open roles

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Your applicationOpen now大模型存储科研实习生sii-czxy/campus

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Share of postings closed within
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  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 44 days ago

The posting

1. 大模型存储系统调研与技术分析：阅读并整理大模型存储系统相关前沿论文与开源项目，包括 LMCache、Mooncake 等，了解大模型训练、推理及智能体运行时中的存储需求与关键技术。 2. 前沿存储系统复现与性能测试：复现代表性大模型存储系统方案，搭建实验环境，完成系统测试、性能评估和结果分析，深入理解大模型基础设施中的存储瓶颈。 3. 存储系统优化方案研究：围绕大模型训推场景开展创新方案探索，包括 QLC SSD 写放大优化、超高性能存储访问（100M IOPS）集成、新型存储架构设计等方向。 4. 系统实验开发与性能分析：参与存储系统原型开发、实验环境搭建和性能调优，分析文件系统、存储设备、GPU 显存、内存以及大模型运行时之间的协同关系。 5. 科研交流与成果整理：参加项目组例会，汇报阶段性研究进展，整理实验数据、技术文档和研究报告，协助推进科研成果产出。

1. 招募对象：本科生、硕士研究生。 2. 计算机科学、计算机系统结构、软件工程等相关专业优先。 3. 了解文件系统、存储系统、大模型运行时、GPU、显存和内存等相关基础知识，对系统软件和大模型基础设施方向具有研究兴趣。 4. 具备 Python 编程基础，熟悉系统编程基本概念；有文件系统、存储系统、操作系统相关开发经验者优先。 5. 能够阅读英文技术资料或相关论文，具备论文复现、实验设计、性能测试和问题分析能力。 6. 有科研项目、论文复现、算法竞赛、系统类竞赛或开源项目经历者优先。 7. 具备 Python 和机器学习基础，了解文件系统、存储系统、大模型运行时、GPU、显存或内存相关知识；对系统开发具有较强兴趣和实践意愿。 8. 具备一定系统方向研究基础，熟悉存储系统、大模型基础设施或高性能计算相关技术，有独立开展实验和分析能力。 9. 具备较强的问题分析能力和工程实践能力，能够稳定投入科研时间，积极参与系统开发、实验验证和技术探索。 10. 实习安排：线上线下结合；周期3–6个月；每周投入20-30小时。

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