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JD.com · 北京市-北京市

# 大模型驱动的库存与调度算法优化

北京市-北京市 Internship or early career 

Listed on JD.com’s official careers site. Posted July 20, 2026. Check that it is still open and apply there.
[Apply on JD.com’s careers site →](https://campus.jd.com/#/details?id=9002)

[OpenNash Jobs](https://jobs.opennash.com/) / [JD.com](https://jobs.opennash.com/companies/jd/) / 大模型驱动的库存与调度算法优化

## Job description

工作职责
- 负责研发基于大模型的仓储订单预测模型，结合强化学习算法实现智能库存优化。
- 研发大模型驱动的设备调度系统，从集群调度向单体调度演进，提升调度精度和效率。
- 研究LLM-as-a-Judge用于自动化评测调度和预测算法效果，建立human-in-the-loop的优化机制。
- 结合大模型预测结果与实际运营数据，持续优化库存与调度算法。
- 探索大模型在物流调度领域的创新应用，结合多模态信息（文本、图片、半结构化数据等）提升算法效果。
- 负责多源异构混合AGV调度算法设计。 任职要求
- 机器学习与运筹优化等相关领域的本硕博在校生。
- 具备扎实的机器学习与强化学习理论基础，拥有卓越的问题抽象与模型调试能力。
- 具备大模型微调实战经验，熟悉主流建模工具（如HuggingFace Transformers）。
- 具备扎实的Python编程能力，熟练使用TensorFlow或PyTorch框架。
- 掌握传统优化算法与AI结合方法，在顶级会议有论文发表经验或具备深度工业实践经验者优先。

## At a glance
- Posted by the employer: Jul 20, 2026
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 91 days
- Location: 北京市-北京市
- Employment type: Internship or early career[Apply on JD.com’s careers site →](https://campus.jd.com/#/details?id=9002)

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