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Open nowPosted 290 days ago

多模态算法实习生-TikTok算法

ByteDance19,268 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now多模态算法实习生-TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.5% 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. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 290 days ago

ByteDance median: 9 days open

The posting

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。 团队介绍：TikTok推荐算法团队，负责国际化短视频产品的基础推荐算法，加入我们，你能接触到包括用户增长、社交、直播、电商C端、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探索，推荐大模型的应用研究等多个学术领域的算法改进以及对多种场景的推荐架构的设计和对产品数据的复杂深入的分析。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；可以跟来自全球不同国家的团队合作, 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、负责字节跳动国际化直播业务中的多模态、计算机视觉、自然语言处理的算法工作，探索内容理解技术在各业务中的应用落地，实现业务指标的增长与技术创新； 2、探索前沿多模态技术研究，结合业务的需求，持续优化算法助力业务增长，具体的技术方向包括但不限于：多模态预训练，多模态检索；多标签视频/文本分类，直播高光识别；多模态大模型/大语言模型SFT/Continue Training；多模态和推荐模型的结合；多模态的开集（Few/Zero-Shot）识别；负责算法的工程部署和应用落地； 3、深入直播推荐业务，利用内容理解技术帮助直播推荐在实时推荐、互动生态、直播创作、兴趣探索、多样性等方向上做得更好； 4、承接直播平台的识别需求，健全直播生态各个维度的内容理解体系，做好直播内容的准确理解。

1、2027届硕士及以上学位在读，计算机、软件工程等相关专业优先； 2、熟悉Linux平台以及常用深度学习框架PyTorch/TensorFlow等； 3、熟悉多模态/计算机视觉/自然语言处理在深度学习上的经典算法，有相关内容理解领域的技术积累； 4、责任心强，积极主动，有良好的沟通能力和团队合作能力； 5、有独立思考以及动手能力，提出想法并能付诸实践验证。

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