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Open nowPosted 694 days ago

多模态大模型算法实习生-AI Music

ByteDance19,260 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now多模态大模型算法实习生-AI MusicByteDance · 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 694 days ago

ByteDance median: 27 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:我们是TikTok研发旗下的音乐算法团队,主要任务是打造优质高效的AI音乐算法和服务。团队的业务与技术产出丰硕:建设了行业领先的音乐识别系统,率先实现了翻唱识别能力在实际业务中的落地;自研音乐理解大模型首创全局与时序理解能力的统一,业务应用广泛;文生音乐模型效果已达行业第一梯队。学术上,团队在AAAI、ICASSP等顶会发表论文20余篇,其中ByteCover和HTS-AT等已成领域经典算法。团队诚邀优秀算法人才加入,共享千卡算力与数亿级用户的全球落地场景。

1、参与音乐大模型的预训练、微调与强化学习等方向的算法研究,构建多模态音乐理解、生成和编辑大模型; 2、参与音乐大模型技术在TikTok等业务中的落地,场景包括但不限于音乐搜推、视频配乐、音乐创作工具等; 3、在音乐与人工智能的交叉领域开展前沿研究,在领域的顶级会议或期刊发表论文。

1、2027届本科及以上学历在读,计算机、软件工程、人工智能等相关专业优先; 2、深入理解多模态内容理解和生成相关技术,有音乐表征学习、音频编解码器、多模态大语言模型、扩散模型等方向的研究经验者优先; 3、熟悉常用的深度学习算法,有较强的数理基础以及代码能力,有强化学习研究经验者优先; 4、在相关国际会议(NeurIPS、ICLR、ACL、IJCAI、AAAI、CVPR、ISMIR、ICASSP等)上发表论文者优先; 5、对AI音乐领域充满热情,有较强的团队协作能力,能与团队紧密合作,共同推进项目进展。

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