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Open nowPosted 208 days ago

【研究型实习生】生成式重排

poizon/578078163 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【研究型实习生】生成式重排poizon/578078 · Shanghai, Chinese Mainland

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  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 208 days ago

The posting

项目描述： 基于transformer、LLM构建重排模型，充分挖掘上下文信息，提升模型预估准确率；通过列表级（List-wise）损失函数、强化学习等手段，优化list级点击、时长、多样性及生态等多目标全局收益； 模型性能优化，通过多 Token 预测（MTP）、KV Cache、模型量化、算子融合等技术，实现高并发下的低延迟推理。 岗位职责： 1. 跟进和设计基于强化学习的生成式Listwise混排框架，重点研究探索多目标reward设计、强化学习优化算法、兼顾激励相容原则等方向； 2. 结合以上方向的探索和研究，撰写发表论文，和业界、学术界保持良好的交流。

1. 2028届及以后毕业，本科及以上学历在读，自然语言处理、机器学习、数据挖掘、人工智能等相关专业； 2. 熟练掌握Tensorflow深度学习框架，扎实的编程基础，具备独立的算法实现能力； 3. 有强化学习实操经验，参与过业界强化学习大规模项目者优先； 4. 良好的逻辑分析能力和数理基础，对算法原理及应用有较深入的理解，在人工智能相关的各类国际顶级会议/期刊中发表过论文者优先

本项目为得物研究型实习生项目。该项目岗位最低实习时长为3个月，岗位非纯业务开发岗位，主要目的为发表顶级期刊。

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