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Kuaishou Technology · Beijing

# 电商推荐算法实习生 - 流量策略方向

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/26381)

[OpenNash Jobs](https://jobs.opennash.com/) / [Kuaishou Technology](https://jobs.opennash.com/companies/kuaishou-technology/) / 电商推荐算法实习生 - 流量策略方向

## Job description
- 参与亿级用户规模的电商推荐优化，提升电商推荐的多目标排序效率，以及电商与其他业务间的混合排序效率；
- 负责机器学习模型优化，包括但不限于深度学习、强化学习、因果推断等，负责机制策略算法优化，包括但不限于调控策略、多目标优化策略、uplift策略、混排机制等，实现电商流量效率的最大化；
- 跟踪业界深度学习、强化学习、博弈出价等领域进展，并结合应用场景快速实验和调优。
- 硕士及以上学历，计算机相关专业；
- 熟悉C++，Python等编程语言，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；
- 熟悉常用机器学习算法，包括机器学习、最优化、因果推断、强化学习等算法原理及应用，有扎实的基础；
- 良好的逻辑思维能力，优秀的分析和解决问题的能力，善于沟通和思考，责任心强，具有很好的团队协作能力。 【加分项】
- 有推荐系统、机器学习、自然语言理解、计算广告及博弈出价相关领域研究或实习经验；
- 在NIPS、ICML、ACL、SIGKDD、RECSYS、WSDM、WWW等相关国际顶级会议上有文献发表；
- 有ICPC、Topcoder Algorithm或类似算法竞赛经历者优先。

## 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/26381)

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