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JD.com · 北京市-北京市

# 生成式推荐与强化学习后训练探索

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=8853)

[OpenNash Jobs](https://jobs.opennash.com/) / [JD.com](https://jobs.opennash.com/companies/jd/) / 生成式推荐与强化学习后训练探索

## Job description

工作职责
- 负责基于内容多模态信号的生成式推荐技术探索与落地。
- 研究生成式推荐架构，探索Scaling Law在生成推荐中的影响因素与效果天花板。
- 探索强化学习在生成式推荐后训练中的各项优化方案。
- 调研不同Reward Model的有效性与建模逻辑，构建可靠的模型效果提升路径。 任职要求
- 计算机科学、深度学习或强化学习等相关领域的本硕博在校生。
- 研究方向需涉及大模型微调、时序预测、强化学习或表征学习中的至少两项。
- 精通PyTorch/TensorFlow框架，具备LLM微调（如HuggingFace/LLaMA）实战经验。
- 熟悉业界主流推荐系统架构与建模原理，熟悉多模态大模型者优先。
- 具备将学术成果转化为工业解决方案的能力，以及优秀的跨团队沟通能力。
- 在NeurIPS/ICML/KDD等顶级会议有推荐相关论文发表经历者优先。

## 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=8853)

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