[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

# 腾讯视频-视频生成模型负责人-(深圳)(杭州)

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=2000481633232375808)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / 腾讯视频-视频生成模型负责人-(深圳)(杭州)

## Job description

### Responsibilities
- 负责腾讯视频影视AIGC方向（涵盖影视视频模型生成、后期编辑等场景）的长期技术路线规划、核心架构设计及模型研发；
- 主导前沿生成模型（如DiT、理解-生成统一架构等）在影视领域的研究与应用，构建具备高真实度、强可控性、长时序一致性的视频生成/编辑模型，攻克影视垂类场景的核心技术难题；
- 作为技术负责人，带领团队持续探索创新，制定技术发展方向，把控项目进度与交付质量，推动团队整体技术能力提升；
- 持续追踪学术界与工业界最新进展（如Sora、Veo、Kling、Runway等），评估并引入前沿技术思想，确保团队在视频生成领域保持技术领先优势。 Requirements 1.计算机科学、人工智能、多媒体或相关专业硕士/博士学历； 2.5年以上算法研发经验，其中近3年深度聚焦于AIGC视频生成/编辑领域； 3.熟练掌握Python，精通PyTorch/TensorFlow等深度学习框架，具备出色的工程实现与代码优化能力； 4.具备扎实的机器学习与深度学习理论基础，对生成模型（Diffusion Model、Flow Matching、auto-regressive、VAE、Transformer等）有深入理解和丰富实战经验； 5.熟悉视频大模型全链路研发流程，包括预训练、后训练（SFT/RLHF/DPO）、高效微调（LoRA等）及高质量数据构建； 6.熟悉大规模分布式训练技术（如DeepSpeed、FSDP、Megatron-LM等），具备千卡级及以上训练调优经验者优先； 7.在视频生成/编辑领域有代表性工作，在CVPR、ICCV、ECCV、NeurIPS、ICLR、ICML、SIGGRAPH等顶会发表过相关论文； 8.具备优秀的沟通表达与跨团队协作能力，有技术引领意识和知识分享热情； 9.对影视内容创作有热情，具备产品思维，能够从业务场景出发推动技术创新。

## 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=2000481633232375808)

## 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/)