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Open nowPosted 83 days ago

激励推荐算法工程师 - TikTok算法

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now激励推荐算法工程师 - TikTok算法ByteDance · Beijing, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on ByteDance's own form.

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The clock on this job

Early applications get read.

11.4% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 83 days ago

ByteDance median: 23 days open

The posting

团队介绍：TikTok搜推算法团队，负责TikTok短视频产品的基础推荐、搜索算法，加入我们，你能接触到包括搜索、用户增长、社交、直播、内容创造、内容消费等核心业务场景，直接为核心用户体验负责，支持产品在全球赛道上高速发展。我们的工作内容包括大规模推荐算法的优化、复杂约束的优化问题的解决、多模态大模型的落地，并着力研究下一代AI Search和Chatbot的核心研发技术，包括不限于Multi-Agent、Agentic RL、Harness、Loop Engineering，探索强化学习在大模型时代的新范式。在这里，你可以深入钻研机器学习算法的改进和优化，探索前沿的技术；可以感受不同文化的碰撞，激发认知；可以通过对产品和内容生态的深度分析，影响产品未来的发展方向。

1、通过因果推断、强化学习、运筹规划等前沿技术，构建用户深度体验的增长模型，优化激励策略的精准性与效率，提升平台商业化价值； 2、设计并落地动态激励系统，平衡短期收益与长期用户价值，驱动用户活跃与留存的正向循环； 3、短视频推荐方向： 1）主导TikTok Pro端融合激励信号与内容兴趣的混合推荐算法研发，解决业界少有的「激励产品×短视频APP」双形态协同难题； 2）构建专属Pro用户的内容理解与增长模型，结合激励行为、创作生态与内容消费数据，打造差异化推荐体验； 3）探索大模型、多目标优化、序列建模等技术在「激励x内容」联合建模中的创新应用，定义下一代增长范式。

1、2027届获得硕士及以上学位，计算机、人工智能、数学、运筹学等相关专业； 2、扎实的编码能力（C++/Python/Scala）与数据结构/算法基础，熟悉分布式系统开发； 3、精通以下至少一个领域：因果推断、运筹优化、强化学习、推荐系统、搜索引擎； 4、熟悉大模型、图神经网络（GNN）、序列建模等技术，有计算广告、激励系统研究实践经验者优先； 5、优秀的分析问题和解决问题能力，强烈的技术热情与创新意识，追求技术落地与业务价值的双重闭环； 6、对复杂业务场景有抽象能力，能独立设计技术方案解决非标准化问题，具备优秀的跨团队协作能力，能以技术语言驱动业务决策。

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