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Kuaishou Technology · Beijing

# 大模型算法实习生-【商业化】

Beijing 

Listed on Kuaishou Technology’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/24902)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 大模型算法实习生-【商业化】

## Job description

### 大模型理解方向
- 探索多模态大模型在视频、图像、文本内容的理解能力，构建场景化模型，提升风险识别准召率； 研究视频/图像拒绝理由的可解释性归因方法，推动人机协同审核应用落地； 构建大模型在风险防控、开户业务等场景的垂类内容理解能力，优化模型对抗性及迭代效率； 开发视频、图文向量化表征技术，提升跨模态检索能力（如视频索引、图文相似性检索）；

### 大模型生成方向
- 研究多模态大模型（图像/视频）生成与修复技术，探索可控内容生成方法，提升风险素材过审率； 构建大模型训练、推理、评测的标准化流程，推动平台化能力建设与自动化迭代；

### 大模型推理部署方向
- 优化大模型推理框架（低延迟、高吞吐），研究量化、剪枝、动态调度等加速技术； 推动多模态大模型在工业级场景的轻量化部署落地。 *根据研究方向选择以上至少一个领域深入参与。
- 计算机科学、人工智能、电子工程等相关专业硕士/博士在读，扎实的算法与编程基础；
- 熟悉多模态大模型（如Transformer、CLIP、ViT等）及生成模型（如Diffusion、GAN）、熟练使用PyTorch/TensorFlow等框架，熟悉分布式训练或模型压缩技术者优先、具备视频处理、跨模态检索、强化学习相关经验者加分；
- 对技术前沿敏感，能独立复现论文算法并改进，有顶会论文发表或竞赛经验者优先；
- 逻辑清晰，责任心强，具备快速学习能力和团队协作意识。

### 加分项

熟悉大模型在风控、内容审核等场景的应用

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 19, 2026
- Last checked: Oct 19, 2026
- Listed for: Under a day
- Location: Beijing[Apply on Kuaishou Technology’s careers site →](https://zhaopin.kuaishou.cn/#/official/social/job-info/24902)

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