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Open nowPosted 122 days ago

推荐大模型算法实习生-抖音

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now推荐大模型算法实习生-抖音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. 4.2%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 122 days ago

ByteDance median: 23 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：Data-抖音团队，负责抖音APP的推荐算法、AI大模型应用、内容算法、智能对话等算法工作，对接全链路各体裁（短视频，直播，图文）各业务（内容消费，UGC，打赏，社交，生态，投稿，消息，汽水音乐，精选，增长投放，评论，内容理解&安全、智能对话等）。我们的工作涉及大规模推荐算法的优化、复杂约束的优化问题的解决、内容理解、LLM技术技术研究、AI落地应用以及新业务方向探索、CV/NLP等多个学术领域的算法改进工作、对多种场景的推荐架构的设计和实现和对产品数据的复杂深入的分析工作。在这里，你可以深入钻研机器学习算法的改进和优化，探索工业界最领先的推荐系统架构和推荐大模型算法、可以通过使用最新的大模型等技术支持抖音的数字人、智能客服、AI工具等创新探索；可以通过对产品的深度理解和思考，将算法应用到业务中去；也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、负责推荐场景下的基础大模型的持续优化，探索模型参数量的Scaling Law，提升模型在复杂推荐场景下的理解与推理能力，推动推荐向Foundation Model范式演进； 2、突破传统“召回-排序”的漏斗式架构，探索并落地结合多模态的生成式召回技术； 3、研发端到端的推荐模型，探索将召回、精排等多个模块统一在一个大模型框架内，构建高效的下一代推荐链路； 4、针对推荐系统中的多维收益（时长、互动、留存等），设计适用于大模型体系的多目标优化方案，实现多场景下的收益最大化。

1、2027届本科及以上学历在读，计算机、数学、统计学、自动化等相关专业； 2、具备扎实的数据结构与算法功底，编程基础扎实； 3、熟练使用Python/C++，熟悉Linux开发环境； 4、熟练掌握PyTorch或TensorFlow等至少一种深度学习框架，有独立实现复杂模型结构的能力； 5、对机器学习、深度学习的基础理论有透彻理解；了解推荐系统、自然语言处理（NLP）或计算机视觉（CV）的基础概念及经典算法（如CTR预估经典模型、序列建模、双塔模型等）；持续关注AI领域尤其是大语言模型（LLM）的发展；了解Transformer架构及主流预训练模型，有开源大模型微调（SFT、RLHF）或多模态相关学术项目经验者优先； 6、具备优秀的逻辑思维能力与自驱力，具备好奇心和快速学习能力；面面对未知和挑战具备积极解决问题的能力；具备良好的沟通表达能力与团队协作精神。

加分项 1、在KDD、NeurIPS、ICLR、ACL、EMNLP、CVPR等人工智能、数据挖掘相关会议有第一作者论文发表； 2、在Kaggle、KDD Cup、天池等国内外数据挖掘或算法竞赛中获得过优异成绩； 3、获得过ACM/ICPC、CCPC等程序设计竞赛区域赛金牌及以上荣誉。

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