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Open nowPosted 84 days ago

多模态大模型算法工程师 - TikTok算法

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now多模态大模型算法工程师 - TikTok算法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 84 days ago

ByteDance median: 27 days open

The posting

团队介绍：TikTok搜推算法团队，负责TikTok短视频产品的基础推荐、搜索算法，加入我们，你能接触到包括搜索、用户增长、社交、直播、内容创造、内容消费等核心业务场景，直接为核心用户体验负责，支持产品在全球赛道上高速发展。我们的工作内容包括大规模推荐算法的优化、复杂约束的优化问题的解决、多模态大模型的落地，并着力研究下一代AI Search和Chatbot的核心研发技术，包括不限于Multi-Agent、Agentic RL、Harness、Loop Engineering，探索强化学习在大模型时代的新范式。在这里，你可以深入钻研机器学习算法的改进和优化，探索前沿的技术；可以感受不同文化的碰撞，激发认知；可以通过对产品和内容生态的深度分析，影响产品未来的发展方向。

1、参与国际化短视频生活服务推荐系统的大模型方案设计与架构创新，推动推荐系统范式向生成式方向升级； 2、负责构建可扩展的推荐大模型（如LargeRecModel、OneRec等），涵盖生成式召回、生成式预估、生成式排序等核心模块； 3、针对推荐场景中的长序列、多跳兴趣建模问题，设计和实现具备Scaling能力的Transformer模型； 4、参与推荐大模型与基础Infra系统的深度协同优化，提升推理效率与推荐精度； 5、深入分析业务数据，理解用户行为和兴趣演化过程，结合生成式技术实现更具解释性和泛化能力的推荐系统； 6、持续关注前沿技术发展方向，参与推荐系统架构的长期技术演进和技术攻坚。

1、2027届获得硕士及以上学位，计算机等相关专业优先； 2、扎实的CV/NLP/多模态建模背景，具备主导或核心参与复杂内容理解系统研发经验；有跨模态对齐、跨语言理解、多语种Embedding等项目经验者优先； 3、熟悉Transformer、SIGLIP、Qwen-VL模型等主流多模态架构，有大规模训练和部署经验； 4、熟悉主流推荐系统架构，了解推荐内容建模与行为建模的结合方式； 5、在CVPR、ACL、EMNLP、NeurIPS、ICLR等会议有论文发表者优先；有强烈的技术热情和团队协作能力，能在复杂系统中快速定位问题并提出解决方案。

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