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Open nowPosted 324 days ago

多模态算法实习生-搜索

ByteDance19,209 open roles

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

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The clock on this job

Early applications get read.

12.1% 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. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 324 days ago

ByteDance median: 2 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：字节跳动搜索团队主要负责抖音、国际化短视频、今日头条、红果短剧、番茄小说、AI搜索等产品以及电商、生活服务等业务的搜索算法创新和架构研发工作。 我们使用前沿的机器学习\大模型技术进行端到端建模并不断创新突破，同时专注于分布式系统、机器学习系统的构建和性能优化，从内存、Disk等优化到索引压缩、召回、排序等算法的探索，致力于支撑字节跳动持续多元化的产品创新和高速的业务增长、基于大模型革新和重塑下一代搜索技术体系，充分给同学们提供成长自我的机会。 主要工作方向包括： 1、探索前沿的NLP技术：全面基于LLM的Query分析、相关性、个性化预估、满意度评估、生成式检索等，全链路应用LLM/VLM，每个细节都充满挑战； 2、跨模态匹配技术：进行多模态预训练，在超大规模的多模态表征、匹配、生成等多个技术方向上持续突破，打造世界领先的多模态搜索系统； 3、大规模流式机器学习技术：应用大规模机器学习，解决搜索中的推荐问题，让搜索更加个性化更加懂你； 4、千亿级数据规模的架构：从大规模离线计算，分布式系统的性能、调度优化，到构建高可用、高吞吐和低延迟的在线服务的方方面面都有深入研究和创新； 5、推荐技术：基于超大规模机器学习、因果推断、大模型推理等技术手段，构建业界领先的搜索推荐系统，对搜索推荐技术进行探索和创新。

1、多模态大模型：基于大规模对比学习，通用Tokenizer，MOE与RL，Long Context建模等VLM模型研究与应用，为抖音生态提供高质量Caption，关键帧，表征，Tokenizer等基建，探索多模态大模型Scaling Law； 2、Al问答/Agent：基于SFT，RL，Context Engineering，Memory等技术迭代Planner/Summary提升AI问答能力，探索解决复杂问题Agent/Adaptive Thinking，视觉世界知只压缩与检索等； 3、大规模视觉搜索：检索，相关性，个性化等算法基于VLM与大模型做技术代际升级，探索结合视觉工具的Agent自动化标注，生成式召回/混排，VLM相关性，多模态表征/个性化CoTrain，Dense个性化，RL Based，GE等技术； 4、基础视觉智能：基于VLM重构视频分析，主体识别，OCR，视频Tracking，细粒度分类等基础视觉算法支撑理解图片/视频理解，探索多任务统一，视觉推理，复杂Context，细粒度视觉理解能力。

1、2027届本科及以上学历在读，计算机专业优先； 2、熟悉CV、VLM、Omni Model、LLM、Agent、DeepResearch、视觉搜索/Al问答等相关的算法和技术； 3、熟悉Linux开发环境，熟练使用C++和Python语言； 4、出色的问题分析与解决能力，由衷热爱技术，愿意探索与思考新技术，有强烈的工作责任心跟自驱力，保持较好的工作状态，优秀的代码能力，数据结构和基础算法功底； 5、有CVPR、ICCV、ICLR、NeurlPS顶会论文优先。

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