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Open nowPosted 2874 days ago

多模态大模型优化工程师-Data AML(北京/上海/杭州/深圳)

ByteDance19,269 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now多模态大模型优化工程师-Data AML(北京/上海/杭州/深圳)ByteDance · Shenzhen, Guangdong, Chinese Mainland
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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 9 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 2874 days ago

ByteDance median: 9 days open

The posting

1、深度参与对字节跳动自研模型Seedance/Seedream/Seed-VLM,以及开源LLM/VLM模型的软硬件协同优化和算法优化,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的加速算法矩阵; 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,并加速训练和推理过程,通过算法和工程创新实现降本增效; 4、探索Efficient AIGC,Efficient LLM领域的问题,结合具体应用场景,通过高质量数据合成、偏好对齐等手段,提升预训练大模型能力和效率,支持公司的基础模型落地; 5、研发业界效果领先的端侧SLLM/SVLM,赋能抖音/剪映等产品的端侧大模型需求,服务全球数十亿用户。

1、硕士学位及以上,计算机、人工智能、软件工程相关专业; 2、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。

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