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Open nowPosted 190 days ago

基于投放信号反馈的Agentic视频生成闭环与应用研究-GenAI（北京/上海/杭州）

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now基于投放信号反馈的Agentic视频生成闭环与应用研究-GenAI（北京/上海/杭州）ByteDance · Beijing, 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 190 days ago

ByteDance median: 27 days open

The posting

团队介绍：GenAI团队专注于开发跨模态生成式AI前沿技术（涵盖文本、图像、视频、落地页等），为广告主、代理商和创作者打造行业领先的创意提效及投放提效解决方案。我们致力于通过生成式AI技术实现创意工作流自动化，全面提升客户商业收益。团队立志引领广告科技与创意产业的生成式AI变革，为全球客户、创作者及整个生态体系赋能并创造价值。

课题介绍：短视频是广告投放的核心，为大幅提升自动化生产水平，本项目计划基于Topads打造一套智能Agent闭环系统。该系统具备深度解析爆款多模态叙事与运镜节奏的能力，能自动调度In-house模型，将新商品自然融入以实现高效复刻。该系统还计划打破传统的开环生成模式，引入真实广告投放信号作为关键反馈。通过RL算法让投放数据直接反哺，持续优化Agent在视频理解、可控生成与低效内容汰换全链路上的决策策略，最终实现高ROI营销视频的规模化生产。

课题挑战： 1、长视频生成中需保持极低错误率与高一致性； 2、需克服投放信号噪声、延迟与长周期特性以优化Agent。

课题价值： 1、打通基于真实投放信号反馈的Agentic理解、生成、汰换闭环； 2、极大提升视频生成自动化程度和质量，实现爆款视频规模化复刻与高ROI转化。

1、2027届毕业，获得博士学位，人工智能、计算机、数学相关专业优先； 2、优秀的代码能力、数据结构和基础算法功底，熟悉PyTorch深度学习等框架； 3、有丰富的研究实践经验；在ICML/ICLR/CVPR/NeurIPS等顶级期刊会议上发表论文者优先； 4、对LLM/VLM/Agent/Video Gen的相关后训练技术，包括微调、RL有实践或创新优化相关经验； 5、出色的问题分析和解决能力，有自主探索解决方案的能力；良好的沟通协作能力，能和团队一起探索新技术，推进技术进步。

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