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

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Trip.com Group jobs](https://jobs.opennash.com/companies/trip-group/) · [Search jobs](/search/)

Trip.com Group · Shanghai

# AI大模型算法专家

Shanghai 

Listed on Trip.com Group’s official careers site. Posted August 4, 2026. Check that it is still open and apply there.
[Apply on Trip.com Group’s careers site →](https://careers.trip.com/#/job-detail?fromId=MJ030333&atsApiType=Moka)

[OpenNash Jobs](https://jobs.opennash.com/) / [Trip.com Group](https://jobs.opennash.com/companies/trip-group/) / AI大模型算法专家

## Job description

岗位职责
- 主导大模型的算法研究、训练调优及工程化落地，提升模型性能和效率；
- 主导大模型压缩、分布式训练、推理加速等技术落地（如量化、MoE、FlashAttention等）；
- 结合业务场景（如对话系统、内容生成、知识推理）设计模型优化方案，解决数据稀疏性、幻觉抑制等挑战；
- 跟踪学术界与工业界最新进展，推动技术成果转化；
- 主导技术方案输出，协同工程团队实现高性能服务部署；
- 参与Agent架构设计，完成整体Agent项目落地。 任职要求 1. 2年以上大模型研发经验，5年以上算法研发经验，3年以上海外工作经验； 2. 精通PyTorch/TensorFlow框架，熟悉分布式训练工具； 3. 深入掌握Transformer架构及衍生技术，有丰富的大模型调优经验； 4. 熟练掌握大模型微调、蒸馏、强化学习等训练技术； 5. 具备完整的大模型训练-部署全链路经验； 6. 熟练掌握Agent架构；
- 积极拥抱大模型等创新技术，有顶会论文发表者优先。

## At a glance
- Posted by the employer: Aug 4, 2026
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 76 days
- Location: Shanghai[Apply on Trip.com Group’s careers site →](https://careers.trip.com/#/job-detail?fromId=MJ030333&atsApiType=Moka)

## More jobs at Trip.com Group

### [-后端开发工程师-](https://jobs.opennash.com/companies/trip-group/jobs/3fd7aa67824d93394856/)

Shanghai

### [AI Agent工程师（酒店BU）](https://jobs.opennash.com/companies/trip-group/jobs/f1cc5f5708e062dd4138/)

Shanghai

### [AI Agent开发工程师](https://jobs.opennash.com/companies/trip-group/jobs/716999cc960252753f0c/)

Shanghai

### [AI Native 产品经理（线路规划·用户体验方向）](https://jobs.opennash.com/companies/trip-group/jobs/61e27b61f5f48d7fd410/)

Shanghai

### [AI Native 设计师](https://jobs.opennash.com/companies/trip-group/jobs/a5bbe7c88620bfd54ab4/)

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/)