[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

# 游戏Ai-Llm大模型算法研究员

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=2079104731317448704)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 游戏Ai-Llm大模型算法研究员

## Job description

### Responsibilities
- 负责LLM在游戏领域的应用落地，包括但不限于游戏智能NPC的对话、决策交互、陪玩等；

### 负责大模型开发的相关工作，包括但不限于
- 数据合成、微调（SFT、蒸馏）、强化（DPO、GRPO）、RAG、多模态LLM（涉及游戏盘面状态）等；
- 负责探索与跟进AIGC前沿技术，结合未来实际应用场景，提供技术解决方案。 Requirements
- 计算机相关专业，硕士及以上学历；
- 熟悉自然语言处理方向基础的理论和方法，了解前沿的深度学习相关算法，在机器学习领域顶级会议发表过高质量论文者优先；
- 熟悉Linux环境开发，熟练掌握Python，熟练使用PyTorch等主流深度学习框架；
- 具备良好的沟通表达能力与团队协作能力；善于分析和解决问题；具备一定的产品思维；较强的自驱力。

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 12, 2026
- Last checked: Oct 19, 2026
- Listed for: 7 days
- Location: Beijing[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=2079104731317448704)

## 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/)