[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

# 策略平台开发工程师-【算法引擎部】

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/30907)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 策略平台开发工程师-【算法引擎部】

## Job description
- 负责实验效率平台开发及实验流程优化，问题排查分析等工作；
- 负责公司核心的推荐服务的白盒化平台及效能工具建设工作；
- 负责推荐类线上问题的排查、实验问题排查，围绕推荐白盒链路、AB实验架构/流程优化，推动各业务问题解决及策略优化；
- 紧跟业务场景，完成日常研发、问题排查链路优化，并通过平台工具开发，推动技术架构升级及业务效率的提升。
- 本科及以上学历，计算机相关专业，至少熟练掌握一门语言，包括Java、C++、Go/python，go/java优先；
- 具备强烈的责任心，良好的沟通能力，良好的团队合作精神，有一定抗压能力。
- 有推荐系统、实验系统、机器学习、信息检索、自然语言理解、算法博弈论相关领域研究及实践经验优先；
- 有线上问题处置流程、白盒化工具、效率工具等建设能力经验优先。

## 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/30907)

## 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/)