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Open nowPosted 1043 days ago

多模态算法实习生-TikTok算法

ByteDance19,258 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.

11.3% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted 1043 days ago

ByteDance median: 23 days open

The posting

日常实习：面向全体在校生，为符合岗位要求的同学提供为期3个月及以上的项目实践机会。 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、负责国际化短视频生活服务推荐系统中的多模态内容建模工作，提升推荐系统对短视频的理解能力； 2、探索跨模态对齐与统一表征学习，打通内容特征（图文音视频）与用户行为数据的语义关联； 3、与推荐系统团队深度协作，推动多模态信号在生成式召回、预估、排序等关键模块中的应用落地； 4、针对生活服务场景中的短视频内容，构建面向多语种、多文化背景的鲁棒内容理解模型；参与模型架构设计与算法创新，持续优化系统在多模态理解、跨语言迁移等关键技术上的表现。

1、本科及以上学历在读，计算机、软件工程等相关专业优先； 2、掌握计算机视觉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，持续跟踪CV领域的最新进展；了解掌握深度学习常用框架PyTorch、TensorFlow等；熟悉Linux平台，有一定计算机基础，具有良好的算法基础和编码能力； 3、责任心强，积极主动，有良好的沟通能力和团队合作能力；有想象力和独立思考能力，提出想法并能付诸实践验证。

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