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Open nowPosted 43 days ago

长上下文模型训练与评测科研实习生

sii-czxy/campus170 open roles

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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. 57.8%60 days
This job: posted 43 days ago

The posting

1. 搭建并维护 4K–256K 长上下文数据构建、模型训练、检查点管理与评测流程。 2. 在统一数据、训练预算和硬件条件下，开展全注意力、滑动窗口注意力、线性/递归注意力、稀疏注意力、Loop 及混合架构等方案的对比实验。 3. 针对长文档理解、代码生成、多文档推理等任务开展模型评测，分析损失、有效上下文长度、吞吐、显存占用和推理延迟等指标。 4. 开展重复实验、消融实验、留出验证及统计建模，研究模型规模、上下文长度与架构设计之间的 Scaling Law 规律。 5. 维护实验代码仓库、配置文件与日志记录，整理实验结果、可视化图表、技术文档及阶段性研究报告。

1. 本科生、硕士研究生。 2. 计算机、人工智能、数学、统计等相关专业背景优先。 3. 熟悉 Python、PyTorch、Linux 和 Git，具备数据处理、实验记录和结果可视化能力。 4. 本科生具备良好的学习能力和实验执行能力；硕士研究生能够较独立运行 GPU 训练与评测任务，分析实验异常和失败案例。 5. 有大模型预训练、分布式训练、长上下文评测、性能分析或统计建模经验者优先。 6. 做事细致，重视实验设计中的变量控制与公平比较，能够稳定投入科研时间。 7. 线上线下结合，实习周期3–6个月，每周预计投入20–30小时。

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