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

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All China Telecom jobs](https://jobs.opennash.com/companies/china-telecom/) · [Search jobs](/search/)

China Telecom · 拉萨市

# 大模型工程师

拉萨市 

Listed on China Telecom’s official careers site. Posted September 6, 2026. Check that it is still open and apply there.
[Apply on China Telecom’s careers site →](https://job.chinatelecom.com.cn/wt/TELE/web/index/webPosition210!getOnePosition?postId=140095&recruitType=1&brandCode=1&columnId=1)

[OpenNash Jobs](https://jobs.opennash.com/) / [China Telecom](https://jobs.opennash.com/companies/china-telecom/) / 大模型工程师

## Job description

### Responsibilities

各类大模型的部署和业务场景的选型 Requirements:
- 具备扎实的机器学习与深度学习理论基础，熟悉 Transformer/Attention 等主流网络架构，了解国内外主流大模型技术路线、产品特性及生态体系（如 OpenAI、DeepSeek、Qwen 等）。
- 熟练掌握 PyTorch、TensorFlow 等至少一种深度学习框架，精通 Python/C++ 编程，熟悉 Linux 系统及 Docker 容器化技术；了解大模型训练、微调（SFT/LoRA 等）、推理部署（vLLM 等）、RAG 检索增强、提示工程及 Agent 智能体开发。
- 具备良好的编程能力、数据分析能力与算法工程化能力，能跟踪大模型前沿研究成果并推动工程落地；执行力强，有团队合作精神，具备较强的抗压能力与学习能力。
- 有大模型训练 / 微调 / 推理项目实践经验，或在 CVPR、NeurIPS、ICML 等国际会议期刊发表论文者优先。

## At a glance
- Posted by the employer: Sep 6, 2026
- First seen by OpenNash: Oct 11, 2026
- Last checked: Oct 18, 2026
- Listed for: 42 days
- Location: 拉萨市[Apply on China Telecom’s careers site →](https://job.chinatelecom.com.cn/wt/TELE/web/index/webPosition210!getOnePosition?postId=140095&recruitType=1&brandCode=1&columnId=1)

## More jobs at China Telecom

### [IT运维与支撑](https://jobs.opennash.com/companies/china-telecom/jobs/998d5544a777eca3ece5/)

拉萨市

### [云网工程师](https://jobs.opennash.com/companies/china-telecom/jobs/45ed881226ba4944cccb/)

拉萨市

### [云网运维管理](https://jobs.opennash.com/companies/china-telecom/jobs/32cb1b90b468c0d71953/)

拉萨市

## Similar jobs at other companies

### [顶尖应届-大模型工程师（测试方向）-手机](https://jobs.opennash.com/companies/xiaomi/jobs/aa43e3d7c101607af932/)

Xiaomi · 北京

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/)