[Skip to main content](#main-content)

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Tencent Holdings jobs](https://jobs.opennash.com/companies/tencent-holdings/) · [Search jobs](/search/)

Tencent Holdings · Shanghai

# 大模型Code/Agent后训练算法研究员-(深圳)or(北京)or

Shanghai 

Listed on Tencent Holdings’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2027548243965145088)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 大模型Code/Agent后训练算法研究员-(深圳)or(北京)or

## Job description

### Responsibilities
- 负责Code和Agent相关数据构建与治理，构建高质量、多样化的Code/Agent训练数据集，搭建数据迭代闭环，通过数据飞轮持续优化数据质量；
- 负责Agent运行环境与训练环境的构建与优化，构建高可用、可扩展的Agent仿真环境，保障Agent训练、测试及落地的稳定性与高效性；
- 负责Agentic RL在Code/Agent场景的训练，参与Agentic RL Infra建设及优化、Agentic RL 算法优化，持续提升Agentic RL训练的效率和稳定性。 Requirements
- 计算机、人工智能等相关专业硕士以上学历；
- 有大规模强化学习、大模型Code/Agent研发相关经验者优先；
- 具有扎实的深度学习算法基础，熟悉深度学习框架和分布式训练推理加速，有实操经验者优先；
- 在多模态/CV/NLP等领域顶级会议（期刊）发表过论文、主导/参与业界知名的开源项目者优先；
- 具备极强的学习能力和技术追求，良好的团队合作和沟通能力。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Jul 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 92 days
- Location: Shanghai[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2027548243965145088)

## More jobs at Tencent Holdings

### [3A修仙RPG游戏-主策划](https://jobs.opennash.com/companies/tencent-holdings/jobs/89e9be0bc8522a47c921/)

Shanghai

### [3A动作冒险游戏-战斗主策划](https://jobs.opennash.com/companies/tencent-holdings/jobs/9a81d086671e92a54e73/)

Shanghai

### [AI Infra研发工程师-上海/北京/深圳](https://jobs.opennash.com/companies/tencent-holdings/jobs/28bf4dec4ecc0f7de3c4/)

Shanghai

### [AI 沙盒体验资深设计师（深圳/上海）](https://jobs.opennash.com/companies/tencent-holdings/jobs/e74c7711c05491c1126d/)

Shanghai

### [AI产品海外解决方案架构师](https://jobs.opennash.com/companies/tencent-holdings/jobs/568fcdcf0fbc33d4bab0/)

Shanghai

OpenNash lists jobs from employers’ own careers sites and does not handle applications.
Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

OpenNash Jobs · Official listings with dates and links to the employer. [Weekly hiring report](/reports/hiring/) · [Methodology](/methodology/)