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Open nowPosted 266 days ago

多模态大模型应用算法实习生-Seed

ByteDance19,260 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now多模态大模型应用算法实习生-SeedByteDance · Shenzhen, Guangdong, 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. 4.3%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 266 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：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、围绕图像理解与问答，参与视觉感知、复杂场景推理、多轮对话等能力建设，打磨模型在真实任务中的效果与稳定性； 2、面向数学、物理、化学等学科题目，参与解题推理算法优化，覆盖几何、绘图、图形构造等多种题型，推动模型在学科解题、作业辅导、讲题陪练等场景的落地； 3、参与多模态Agent的工具调用（检索、计算、代码执行、领域工具等）、长链路规划、反思纠错、记忆机制等能力研发，推动复杂任务的端到端求解体验； 4、参与Post-training全链路优化，开展SFT、RL、Reward Model等核心算法的调优与创新，围绕豆包App真实业务场景进行定向能力打磨，提升模型在真实任务中的效果； 5、数据链路与评测体系建设：参与多模态数据的采集、清洗、合成、标注规范设计、负面案例归因与评测集建设，支撑SFT/RL/评测的高质量数据闭环。

1、2027届硕士及以上学位在读，人工智能、计算机、自动化、数学等相关专业优先； 2、扎实的数据结构与算法基础，熟练掌握Python和PyTorch； 3、具备良好的数据处理与分析能力（如Pandas/SQL/数据清洗经验），能够独立完成数据Pipeline与实验脚本的搭建和迭代； 4、良好的英文读写能力与数学基础，具备学习能力与论文复现能力，责任心强，积极主动，具备良好的沟通与团队协作能力。

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