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Open nowPosted 595 days ago

多模态世界模型评测算法实习生-Seed

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now多模态世界模型评测算法实习生-SeedByteDance · Beijing, 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 595 days ago

ByteDance median: 23 days open

The posting

日常实习：面向全体在校生，为符合岗位要求的同学提供为期3个月及以上的项目实践机会。 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、建立建立下一代多模态模型评测体系，引导模型向AGI的方向发展： 1）创建针对推理与交互的下一代多模态模型评测Leaderboard； 2）包括而不限于长视频高帧率评估、视频流式交互评估、视觉CoT评估、世界模型评估方法； 3）GUI/游戏等虚拟世界的通用多模态Agent评估方法； 2、探索多模态大模型能力边界： 1）追踪业界对于模型能力的边界拓展进程； 2）持续迭代复杂度更高的评测集合； 3）防止基准测试饱和模型过拟合； 3、优化评测工程链路与评测手段： 1）探索自动化评测任务构造和自动化评估方法； 2）提升模型评测效率。

1、本科及以上学历在读，计算机、电子、数学等相关专业优先； 2、在计算机视觉、多模态、AIGC、机器学习、渲染生成等一个或多个领域有较深入的研究者； 3、具有出色的分析、解决问题的能力，能深入解决大模型训练、应用存在的问题，有自主探索解决方案的能力者； 4、具有良好的沟通协作能力，工作积极主动，能够与团队融洽合作，一起探索新技术，推进技术进步。

加分项： 1、在多模态、大模型、基础模型、世界模型等领域，主导过大影响力模型评测项目者优先； 2、具有优秀的基础算法、扎实的机器学习基础，熟悉CV、AIGC、NLP、RL、ML等领域的技术，在CVPR、ECCV、ICCV、NeurIPS、ICLR、SIGGRAPH或SIGGRAPH Asia等会议/期刊上发表论文者优先； 3、具有优秀的代码能力，熟练掌握C/C++或Python编程语言，ACM/ICPC、NOI/IOI、Top Coder、Kaggle等比赛获奖者优先。

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