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Open nowPosted 83 days ago

Tako AI Agent算法工程师 - TikTok算法

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen nowTako AI Agent算法工程师 - TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 27 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%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: 27 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、Agent Learning与模型能力扩展：研究Agent如何从真实任务Trajectory、环境反馈和用户反馈中学习，结合Post-training、Test-time Scaling、RL Scaling等方法，提升模型在任务拆解、信息获取、工具使用、决策路径、失败恢复和复杂泛化上的能力； 2、个性化Agent：研究用户长期兴趣、上下文、行为反馈和场景状态建模，让Agent能够理解不同用户的需求、偏好和决策习惯，提供因人而异的智能体验； 3、Auto Research与自进化闭环：研究模型如何自动发现问题、获取信息、生成假设、验证结果，并将成功/失败轨迹沉淀为数据、Reward、Benchmark和策略迭代信号，形成持续进化的能力闭环； 4、TikTok生态中的复杂任务智能：结合TikTok视频、评论、创作者内容、热点、经验决策、本地生活、电商等场景，研究Agent如何理解内容语境、整合多源信息、辅助用户比较判断，并完成从信息获取到决策支持的复杂任务。

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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