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Open nowPosted 262 days ago

推荐大模型系统研发实习生-Data AML

ByteDance19,258 open roles

Where
Hangzhou, Zhejiang, Chinese Mainland
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Your applicationOpen now推荐大模型系统研发实习生-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 262 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、扩大推荐模型的行为序列长度、参数规模和训练规模,验证推荐领域的Scaling Law; 2、在亿级用户产生的数据上,构建推荐专用生成式模型的训练系统和推理系统; 3、构建跨业务、跨端的推荐基座大模型,通过蒸馏的方式,赋能多个业务的下游模型; 4、引入文本、图片、视频等多模态信号,增强推荐模型的信息输入,与协同信号联合训练; 5、构建LLM的CPT/SFT/RL系统,与推荐模型深度融合、联合训练,推进LLM4Rec的落地; 6、构建ND-Parallel并行库,支持超大规模的并行训练,优化训练效率,提升万卡集群的训练稳定性,研究业界领先的高性能计算技术、分布式计算技术和深度学习技术,不断提升系统的规模和性能上限。

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、具有扎实的数据结构、算法和计算机体系结构基础,熟练掌握C++/Python/CUDA/Triton中至少一种语言,具备优秀的编程习惯和系统设计能力,能够编写高性能、可扩展的代码; 3、深入理解TensorFlow、PyTorch、JAX等主流深度学习框架底层原理,有算子开发、性能调优或分布式训练实战经验; 4、熟悉大规模分布式系统的设计与开发,了解常用的并行策略(数据并行、模型并行、专家并行、序列并行、流水线并行等)和并行库(DeepSpeed,Megatron等); 5、了解经典的搜广推算法(如DeepFM,DLRM,DIN等),了解主流的LLM技术(如Transformer,BERT,MOE,CLIP等); 6、对挑战性问题(如超长序列建模、万卡规模稳定性)有强烈的探索欲望,具备优秀的逻辑思维能力、独立解决问题的能力,以及团队合作精神。

加分项 1、大模型实战:具有100B+规模大模型的预训练、微调或强化学习经验,深度优化过分布式训练系统的性能; 2、多模态经验:具有多模态表征学习经验(如CLIP,BLIP,VLM),能够将视觉/文本特征有效融入推荐系统; 3、底层优化:熟悉GPU架构,具备CUDA/Triton/Pallas编程经验,深入研究NCCL、RDMA和网络通信优化; 4、框架剖析:深入研究过一种机器学习框架(TensorFlow/PyTorch/JAX或其他自研框架)的代码和设计; 5、顶会论文:在RecSys,MLSys,NeurIPS,ICML,ICLR,KDD,SIGIR,CVPR等AI顶会有高质量论文发表; 6、开源贡献:知名开源项目(如训练框架、并行库、高性能计算库)的核心贡献者,或拥有高质量个人开源项目;竞赛经历:在ACM-ICPC、Kaggle、天池等顶级算法竞赛中,或RecSys Challenge、KDD Cup、NeurIPS Competitions等顶会竞赛中,获得过优异成绩。

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