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Open nowPosted 198 days ago

机器学习系统SRE工程实习生-Seed大模型人才实习

ByteDance19,257 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now机器学习系统SRE工程实习生-Seed大模型人才实习ByteDance · Beijing, 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 16 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 198 days ago

ByteDance median: 16 days open

The posting

团队介绍:字节跳动 Seed 团队成立于 2023 年,致力于寻找通用智能的新方法,追求智能上限,为科技和社会发展作出贡献。 Seed 团队在 AI 领域拥有长期愿景与决心,团队研究方向涵盖 MLLM、GenMedia、AI for Science、机器人等,在中国、新加坡、美国等地设有实验室和岗位。目前,团队已推出业界领先的通用大模型以及前沿的多模态能力,支持豆包、即梦、TRAE 等超过 50 个应用场景,并通过火山引擎开放给企业客户。第三方数据显示,豆包 App 用户量在中国市场排名第一,豆包大模型日均 Token 调用量行业领先。

1、参与大规模生成式AI(LLM、文生图、文生视频等)训练系统与异构推理系统的辅助开发、测试与维护,协助解决系统稳定性、性能优化相关基础问题; 2、协助设计并优化资源调度体系,参与调度策略的落地与验证,学习提升资源利用率、优化调度效率的核心方法,支撑多类型AI任务的精细化管理; 3、参与大规模高速网络(RDMA)、异构算力集群(GPU/国产算力)的部署、运维与监控,学习集群拓扑规划、网络带宽优化、算力资源管理的相关技术; 4、协助高性能存储系统的选型、测试与运维,了解存储IO性能优化、数据可靠性保障的核心逻辑,适配大规模AI训练与推理的数据存取需求; 5、参与训推算力并池混部、离线推理算力提效相关项目的辅助开发,学习算力运营、成本管控的基础方法,沉淀技术实践经验; 6、协助搭建训推全链路的监控、告警体系,参与生产环境简单技术问题的排查与处理,培养故障分析与解决能力; 7、对接算法、业务团队,学习输出MLOps相关技术文档,参与工程化最佳实践的沉淀,推动团队技术知识的传承与分享。

1、2028届及以后本科及以上学历在读,计算机科学、软件工程、人工智能、电子信息等相关专业优先; 2、掌握Python/Go/Shell中至少一种编程语言,具备扎实的编程基础,能够独立完成简单的自动化脚本开发; 3、了解Linux操作系统基础,熟悉常用的Linux命令,具备基础的Linux环境开发与运维意识; 4、对机器学习系统、容器化技术(Docker/Kubernetes)、高速网络(RDMA)、分布式存储等任一领域有一定了解或浓厚兴趣,愿意深入学习; 5、具备良好的学习能力、逻辑思维能力和问题分析能力,能够快速接收新知识、适应技术节奏; 6、具备强烈的责任心、自驱力和团队协作精神,善于沟通表达,愿意主动探索AI工程化领域的前沿技术。

加分项: 1、了解LLM、文生图等生成式AI模型的基本原理,有相关模型训练、部署的课程实践或个人项目经验; 2、熟悉Kubernetes生态,有容器编排、集群管理的基础实践经验(如校园项目、课程设计); 3、了解分布式系统、高速网络(RDMA)或高性能存储的基本原理,有相关技术调研或实践经历; 4、参与过AI相关竞赛、开源项目,或有技术博客、代码仓库(如GitHub)可展示; 5、具备良好的英语阅读能力,能够快速阅读技术文档、跟进前沿技术动态。

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