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Open nowPosted 188 days ago

多模态大模型优化实习生-Data AML

ByteDance19,258 open roles

Where
Hangzhou, Zhejiang, Chinese Mainland
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Your applicationOpen now多模态大模型优化实习生-Data AMLByteDance · Hangzhou, Zhejiang, Chinese Mainland

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The clock on this job

Early applications get read.

11.4% 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. 11.4%7 days
  4. 17.5%14 days
  5. 34.2%30 days
  6. 43.5%60 days
This job: posted 188 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 AML是字节跳动的机器学习中台，为抖音/今日头条/西瓜视频等业务提供推荐/广告/CV/语音/NLP的训练和推理系统。为公司内业务部门提供强大的机器学习算力，并在这些业务的问题上研究一些具有通用性和创新性的算法。同时，也通过火山引擎将一些机器学习/推荐系统的核心能力提供给外部企业客户。

1、深度参与业界效果领先的生成模型Seedance/Seedream相关工作，理解模型Seed-VLM的软硬件协同优化和算法优化逻辑，构建业界领先的模型优化能力矩阵； 2、研发面向多端异构平台的量化&稀疏、MOE压缩、Token压缩、Cache复用、投机解码、KV Cache压缩等加速算法，构建Training-Free或结合Post-Training/RL-Training的加速算法能力； 3、面向分布式训练/推理场景，深度挖掘模型表示位宽、分辨率、步数、结构等维度的冗余，通过算法和工程创新加速训练和推理过程，实现降本增效； 4、探索Efficient AIGC、Efficient LLM领域最前沿的问题，包括多模态理解生成统一建模加速、结合RL训练的模型优化等方向。

1、2027届硕士及以上学位在读，计算机/人工智能/软件工程相关专业优先； 2、实习时间6个月以上，具备优秀的编程能力，扎实的数据结构和基础算法功底，熟练掌握Python，熟悉深度学习框架（如PyTorch），有CUDA/Triton使用经验者优先； 3、在计算机视觉、深度学习领域顶级期刊或会议（如CVPR、ICCV、NeurIPS、PAMI等）发表过论文者优先；对扩散模型、视觉Transformer或生成式AI有深入研究者优先； 4、熟悉扩散模型优化和自回归理解模型的优化技术（如步数蒸馏，高效模型结构设计）、模型优化（如量化、剪枝、稀疏化），了解推理加速（如算子优化、分布式推理、多卡并行等）； 5、具备优秀的问题分析与解决能力，能够自主探索并设计创新性解决方案；具备良好的沟通与协作能力，能够与团队成员共同探索新技术，推动研究进展与项目落地； 6、具备AIGC/LLM/VLM的SFT/RL训练经验，数据清洗经验者优先。

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