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

[OpenNash Jobs](https://jobs.opennash.com/)
[Hiring report](/reports/hiring/) · [All Kuaishou Technology jobs](https://jobs.opennash.com/companies/kuaishou-technology/) · [Search jobs](/search/)

Kuaishou Technology · Beijing

# AI数据架构实习工程师

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/24406)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / AI数据架构实习工程师

## Job description
- 负责研发快手的机器学习平台，作为公司级的平台，支撑了包括推荐、广告、搜索等核心业务的算法迭代；
- 通过自研大数据引擎，构建特征工程领域的高性能计算存储框架和统一开发平台，支持算法团队的研发效率；
- 重点研究海量数据的存储与传输格式，分布式计算框架，算法DSL语言，TaskFlow 等技术，不断优化模型工程的系统效率。
- 本科及以上学历，计算机相关专业优先；

### 编程技能
- 至少熟练掌握Java或C++中的一门编程语言，扎实的计算机基础功底；
- 熟悉 Flink/Hive/HDFS等数据系统的基本原理，有源码级经验者优先；
- 热爱技术，有较好的学习能力、沟通表达能力和团队协作意识；
- 开源社区活跃贡献者优先，有NOI/ACM等相关竞赛经验者优先。

## 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/24406)

## More jobs at Kuaishou Technology

### [(大模型专项）多模态大模型算法工程师](https://jobs.opennash.com/companies/kuaishou-technology/jobs/98edf462c05648daadcf/)

Beijing

### [AI Agent 开发实习生（电商在线推荐引擎）](https://jobs.opennash.com/companies/kuaishou-technology/jobs/5945a85b9a833fcbb5f8/)

Beijing

### [AI Agent 策略实习生](https://jobs.opennash.com/companies/kuaishou-technology/jobs/b814e14328b750da25f6/)

Beijing

### [AI Agent算法专家](https://jobs.opennash.com/companies/kuaishou-technology/jobs/0e36be4e740de43e02ad/)

Beijing

### [AI Agent算法专家（智能创作方向）](https://jobs.opennash.com/companies/kuaishou-technology/jobs/41a78c4c892cbbd1bc50/)

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/)
