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Open nowPosted 86 days ago

搜索算法工程师 - TikTok算法

ByteDance19,208 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now搜索算法工程师 - TikTok算法ByteDance · Beijing, Chinese Mainland

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

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 86 days ago

ByteDance median: 2 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、LLM for Search：探索前沿AI技术，用LLM重构搜索相关性、Query理解、内容理解、语义匹配、结果组织和体验建模，提升搜索系统对复杂意图和内容语义的理解能力； 2、推荐大模型与搜推一体化：构建面向搜索和推荐的统一建模体系及Scaling Law，融合主动意图、长期兴趣、实时行为、内容语义和反馈信号，提升系统对用户与场景的理解能力； 3、生成式搜索：面向复杂、开放和决策型搜索需求，研究复杂需求理解、生成式建模、LLM4Rec、Agentic Search和搜索场景下的RL/Feedback Learning，让搜索具备更强的信息组织、推荐式结果生成和任务完成能力； 4、多模态内容理解：建模视频、图像、文本、语音、评论、标题等多源信号，让搜索系统理解内容生态，而不是只依赖文本索引； 5、大规模搜索学习系统：研究模型训练、在线推理、持续学习、效果评估和系统效率，让前沿模型能力稳定服务全球搜索体验。

1、2027届获得本科及以上学历，计算机、人工智能、数学、统计、电子信息等相关专业优先； 2、算法、数据结构、机器学习和深度学习基础扎实，具备优秀的代码实现和实验分析能力； 3、在搜索、推荐、大模型、多模态或生成式AI中至少一个方向有深入积累； 4、能把真实产品问题抽象成可学习、可优化、可验证的算法问题，而不是只复现论文或调用框架； 5、能在大规模数据和真实系统约束下验证算法价值，理解效果、效率和体验之间的Trade-off； 6、对AI如何重构Search、Recommendation和Discovery有判断力，愿意挑战没有标准答案的问题。

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