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Open nowPosted 122 days ago

【实习】基于多模态大模型与用户行为理解的下一代分发与交互技术-抖音

ByteDance19,260 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【实习】基于多模态大模型与用户行为理解的下一代分发与交互技术-抖音ByteDance · Shanghai, 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. 4.2%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 122 days ago

ByteDance median: 27 days open

The posting

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。

课题介绍： 本课题旨在探索基于多模态大模型的模态理解与表征、世界知识、推理等能力，并深度的与信息分发（推荐、搜索等）中的用户行为理解和建模结合起来，构建支撑下一代分发与交互技术的基础模型和系统范式。通过基础技术突破和探索，既尝试解决原有分发技术中对长尾兴趣分发、用户复杂意图理解、多模态与行为协同融合、System Bias、分发系统的算力与推理分配等一系列关键问题，也探索基于新的多模态大模型与用户对齐的理解，支持全新的可对话性需求满足、可自然交互性的分发调节与个性化等能力和产品形态上的突破。

课题挑战： 1、多模态大模型的完整流程的训练，以及与大规模用户行为深度理解和对齐； 2、突破多模态大模型与长序列高并发高效推理的瓶颈； 3、实现大模型泛化推理能力与复杂推荐业务目标的深度对齐。

课题价值： 1、打破信息茧房，提供个性化可解释推荐，提升长尾/冷启分发效率； 2、沉淀大模型Scaling Up范式，重塑大模型时代的下一代推荐系统； 3、探索全新的支持下一代交互场景的分发基础技术突破。

1、2027届及以后毕业，博士在读；人工智能、计算机、数学相关专业优先； 2、优秀的代码能力、数据结构和基础算法功底，熟练C/C++（传统编码方向）或Python（智能编码方向）； 3、智能编码方向要求有扎实的机器学习基础，在TPAMI/CVPR/NeurIPS/ICCV等期刊会议上发表论文者优先； 4、有向标准组织提出过提案并有标准会议经验的同学优先； 5、出色的问题分析和解决能力，有自主探索解决方案的能力，良好的沟通协作能力，能和团队一起探索新技术，推进技术进步； 6、出色的心理素质与应变能力，面对困难勇于迎接挑战；面对复杂局面沉着、冷静、灵活。

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