[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

# 支付增长算法工程师

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/23185)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 支付增长算法工程师

## Job description
- 深入快手支付业务场景，参与支付用户增长、支付渠道推荐、流量分发、保险业务等场景的算法研发，提升快手支付业务用户增长和平台营收；
- 负责支付业务各算法场景的技术攻关，参与机器学习、深度学习领域的核心研发工作，包括但不限于神经网络模型的设计与优化，营销uplift模型、归因模型等的算法和系统研发；
- 针对快手平台海量用户行为和画像数据，结合支付业务约束和诉求，设计针对性的多目标优化策略、运筹优化策略和推荐策略，提升用户转化效率。
- 硕士及以上学历，计算机、数学或统计学相关专业；
- 熟悉Linux环境、C++和Python语言，良好的逻辑思维能力，优秀的编码能力，扎实的数据结构和算法功底；
- 具有深度学习、机器学习、运筹优化、数据挖掘等相关领域知识；
- 善于阅读文献，快速学习 ，具备优秀的分析和解决问题的能力，良好的沟通协作能力；
- 有支付财经算法、广告投放优化、智能营销、个性化推荐相关经验者优先。

## 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/23185)

## 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/)