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JD.com · 北京市-北京市

# 购物智能体强化学习后训练算法探索

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=8934)

[OpenNash Jobs](https://jobs.opennash.com/) / [JD.com](https://jobs.opennash.com/companies/jd/) / 购物智能体强化学习后训练算法探索

## Job description

工作职责
- 面向复杂电商购物智能体场景，研究多轮工具调用与长链路决策下的强化学习核心问题。
- 攻坚稀疏奖励建模、信用分配及策略优化稳定性等技术瓶颈，探索新型Agentic RL算法落地。
- 深度挖掘海量用户行为日志，设计面向转化目标的多粒度Reward信号体系。
- 建立并完善面向购物Agent的系统性评测体系，以评测驱动模型能力持续演进。 任职要求
- 计算机科学、人工智能或机器学习等相关领域的本硕博在校生。
- 具备扎实的强化学习理论基础，熟悉PPO、GRPO、DPO等主流前沿优化算法。
- 具备优秀的工程代码能力，熟悉PyTorch及大规模分布式计算，拥有大厂相关实习经验者优先。
- 在Agent训练、工具调用（Tool-use）或多步推理相关方向有扎实的实战工作经验。
- 拥有大模型后训练实操经验，或在相关领域顶级会议有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=8934)

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