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Open nowPosted 282 days ago

流媒体AI策略算法实习生-TikTok研发

ByteDance19,258 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now流媒体AI策略算法实习生-TikTok研发ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

15.1% 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. 2.4%1 day
  2. 6.5%3 days
  3. 15.1%7 days
This job: posted 282 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：TikTok研发团队，旨在实现TikTok业务的研发工作，搭建及维护业界领先的产品。加入我们，你能接触到包括用户增长、社交、直播、电商C端、内容创造、内容消费等核心业务场景，支持产品在全球赛道上高速发展；也能接触到包括服务架构、基础技术等方向上的技术挑战，保障业务持续高质量、高效率、且安全地为用户服务；同时还能为不同业务场景提供全面的技术解决方案，优化各项产品指标及用户体验。 在这里， 有大牛带队与大家一同不断探索前沿， 突破想象空间。 在这里，你的每一行代码都将服务亿万用户。在这里，团队专业且纯粹，合作氛围平等且轻松。目前在北京，上海，杭州、广州、深圳分别开放多个岗位机会。

1、设计智能决策引擎，负责直播/RTC场景中客户端的AI驱动自适应策略研发； 2、运用强化学习（RL）、时间序列预测等轻量级模型，重构传统的ABR、网络带宽预测、性能降级与播控、缓冲策略，打造端侧感知与自适应联动的“智能大脑”； 3、负责服务端转码与调度策略的智能演进，探索基于ML、大模型的动态转码资源调度与画质增强策略，实现体验与成本的全局最优（帕累托最优）； 4、开展数据驱动的个性化QoE建模，突破传统QoS/QoE映射规则局限，依托海量流媒体数据，运用因果推断与大模型（LLM）技术深度分析用户意图与复杂网络环境，构建“千人千面”的个性化体验评价模型，让策略系统具备自我进化能力。

1、2027届硕士及以上学位在读，计算机科学、人工智能、数据科学或相关专业优先； 2、扎实的编码基础，熟练掌握C++/Python，熟悉PyTorch或TensorFlow等主流深度学习框架； 3、对机器学习、强化学习、因果推断有扎实的理论基础；在大模型（LLM/VLM）、生成式AI等领域有探索热情，有相关顶会期刊或实际工程落地经验者优先； 4、对直播/RTC系统的基本架构（如推拉流链路、编码器原理）有一定了解者优先； 5、具备较强的技术好奇心与创新思维，对“用AI重塑传统流媒体基础设施”充满热情，能够在复杂的音视频工程链路中准确界定模型能力边界并推动落地。

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