[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 · Beijing

# 混元强化训练框架研发工程师（深圳/北京/上海）

Beijing 

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=2061810859658887168)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 混元强化训练框架研发工程师（深圳/北京/上海）

## Job description

### Responsibilities
- 参与Research场景下Agent框架的研发与维护，支持强化学习、数据生成及自动化评估等业务需求；
- 负责优化框架的易用性与稳定性，解决实际运行中的性能瓶颈，保障实验流程的高效执行；
- 支持各类外部Agent策略及评估逻辑的接入，维护相关接口与组件，确保系统的兼容性与扩展性；
- 结合大模型训练视角，配合算法团队进行新Agent范式的工程化落地与探索。 Requirements
- 具备扎实的Python编程能力，熟悉异步编程（Asyncio）及并发处理的最佳实践，有良好的代码规范意识；
- 熟悉大模型与Agent相关应用技术，熟练使用AI编程工具并理解其工作原理；
- 熟悉K8S及容器化技术，具备相关环境下的开发或部署经验；
- 了解大模型训练全流程（如预训练、SFT、RLHF）及基本原理；
- 具备良好的问题分析及解决能力、沟通合作能力，有较强的Owner意识。

## 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: Beijing[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2061810859658887168)

## More jobs at Tencent Holdings

### [3D动作游戏《狩》-后台开发-UE5 DS后台开发](https://jobs.opennash.com/companies/tencent-holdings/jobs/6d535d770b7d94786b5e/)

Beijing

### [AI infra研发工程师(北京/深圳)](https://jobs.opennash.com/companies/tencent-holdings/jobs/eda44bea14836b2b9952/)

Beijing

### [AI ⽹络集合通信库运营⼯程师](https://jobs.opennash.com/companies/tencent-holdings/jobs/59f91606e7bdc470bf0b/)

Beijing

### [Aigc内容检测算法工程师（图像与视频方向）](https://jobs.opennash.com/companies/tencent-holdings/jobs/ca1cf721bb29a8df9bdf/)

Beijing

### [AI智能体评测高级工程师](https://jobs.opennash.com/companies/tencent-holdings/jobs/9312d7b2c30640f3f245/)

Beijing

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/)
