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Open nowPosted 6 hours ago

AI搜索算法工程师（Top1方向） - TikTok算法

ByteDance18,760 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowAI搜索算法工程师（Top1方向） - TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 9 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 6 hours ago

ByteDance median: 9 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、AI Search与Deep Search能力建设：面向复杂、高难度搜索需求，研究Query理解、任务规划、问题拆解、多轮检索、信息整合与答案生成等关键技术，提升Search Agent解决复杂问题的能力与边界； 2、大模型训练与生成质量优化：参与搜索回答模型的数据构建和Post-training，结合SFT、Reward Model、RL/OPD等方法，持续优化答案的事实准确性、需求满足度、信息密度、可读性及多语言表现； 3、多模态与个性化搜索体验：结合丰富的视频、图文、评论及用户行为数据，探索跨模态检索、富媒体回答、用户理解与个性化生成，为不同用户提供更直接、更自然的搜索体验； 4、AI搜索全链路优化与规模化落地：参与从意图识别、内容召回与排序、答案生成到质量评估和线上策略的端到端建设，在全球多语言、大规模流量场景下，持续提升产品覆盖率、回答质量、系统稳定性和推理效率； 5、前沿技术探索与产品创新：跟进并实践Agent Learning、Test-time Scaling、强化学习和自进化数据闭环等前沿方向，推动技术成果快速落地到搜索问答、复杂任务解决及新型AI搜索产品中。

1、2027届获得本科及以上学历，计算机、人工智能、数学、电子信息等相关专业优先； 2、具备扎实的机器学习、深度学习和自然语言处理基础，熟悉PyTorch、TensorFlow等训练框架； 3、熟悉大语言模型的训练与优化方法，了解SFT、DPO、PPO、GRPO等后训练或强化学习算法； 4、能分析Agent的完整行为链路，从任务轨迹、反馈信号、策略选择和失败模式中定位问题； 5、实验能力强，能设计Benchmark、拆解Failure Mode，并判断模型提升是否真实、稳定、可泛化； 6、不满足于复现论文或堆技术词，能把真实用户问题抽象成可验证、可迭代、可规模化的算法问题。

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