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Open nowPosted 39 hours ago

内容理解与推荐算法实习生 - TikTok算法

ByteDance19,208 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now内容理解与推荐算法实习生 - TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 39 hours 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。

ByteIntern：面向2027届毕业生（2026年9月-2027年8月期间毕业），为符合岗位要求的同学提供转正机会。

1、多模态内容理解与表征：融合视频、图像、音频、文本、ASR/OCR及用户互动信号，研究基于LLM/VLM的内容语义理解、知识抽取与统一表征； 2、内容理解与推荐联合建模：对齐内容语义、用户行为及协同信号，探索内容理解能力在召回、粗排、精排和多任务学习中的应用； 3、用户兴趣与长期价值建模：结合长序列行为和实时反馈，研究用户长期偏好、短期意图及兴趣迁移，并探索兼顾消费体验与生态价值的优化方法； 4、大模型训练与高效落地：参与业务Post-training、模型蒸馏。

1、2027届本科及以上学历在读，计算机科学、人工智能、机器学习等相关专业； 2、具备扎实的机器学习、深度学习和数据结构基础，熟练使用Python、PyTorch等工具； 3、熟悉机器学习、自然语言处理、数据挖掘中的一项或多项；熟悉推荐系统、计算机视觉或多模态学习者优先； 4、具备良好的论文阅读、问题分析、算法实现和实验验证能力，能够从真实业务问题中抽象研究课题； 5、对推荐算法和多模态大模型有热情，乐于思考和创新，具备良好的沟通表达与团队协作能力，具备较强的自驱力； 6、有推荐系统、LLM/VLM、强化学习或大规模模型训练经验者优先；有顶会论文、高质量开源项目或竞赛成果者优先。

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