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Kuaishou Technology · Beijing

# 大模型评测实习生

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/27510)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 大模型评测实习生

## Job description
- 以算法视角，参与快手大模型（包括不限于LLM、T2I、T2V、I2V、MLLM模型）评测工作和评测体系建设；
- 参与评测相关自动化评测工具开发及维护，最大化提高评测效率；
- 以算法手段，对基座大模型和AI Native应用进行分阶段、端到端评测；
- 参与构建评测Agent工具链、对战平台、模型竞技场、模型效果判别模型、应用数据飞轮等工具链建设。
- 本科及以上学历，计算机、人工智能、大数据、统计等相关专业优先；
- 算法基础扎实，熟悉 Transformer、Bert、DiT、CLIP、CNN、GAN、VAE、Diffusion Models等AI模型基本原理；
- 具备良好的数据化思维，能够基于数据分析结果给出分析结论，熟悉ACC、AUC、F1、recall等基本的模型评估指标计算方式；
- 熟悉常见的模型架构，能够训练或微调常见CV、NLP、LLM、MLLM模型；
- 良好的沟通能力和团队协作精神，严谨的工作态度与高质量意识，对大模型技术有热情和探索精神；
- 具备良好的视野，善于学习新的知识、阅读论文、动手能力强、有进取心。

### 加分项
- 有顶会论文、国家或国际奖项、专利获得者、算法竞赛获奖者优先考虑；
- 实际参与过AIGC、大模型相关的项目研发优先；
- 了解分布式系统、调度、容器、代码管理相关领域技术，熟悉Kubernetes、Docker、Yarn等原理与应用；
- 熟悉常见模型评测数据集、评测方法，包括但不限于C-Eval、CMMU、MT-bench、MINT、SuperCLUE；
- 熟悉Bert、CLIP、BLIP、ResNet、VGG、RCNN、Yolo等常见算法原理及训练实操。

## 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/27510)

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