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Open nowPosted 55 days ago

算法工程师（下一代社区交互：大模型驱动的意图理解与个性化分发推荐方向） - TikTok算法

ByteDance19,208 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now算法工程师（下一代社区交互：大模型驱动的意图理解与个性化分发推荐方向） - TikTok算法ByteDance · Beijing, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. ByteDance postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 55 days ago

ByteDance median: 2 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、NLP与大模型应用：全链路应用LLM/VLM，基于大模型重构内容理解、用户兴趣建模、内容与人的相关性预估、个性化推荐与满意度评估——从建模范式到线上落地，每一个细节都是值得深挖的技术命题； 2、跨模态匹配技术：主导超大规模多模态预训练，在多模态表征、匹配、生成等方向持续突破，打造世界领先的多模态检索与推荐系统； 3、大规模流式机器学习：用大规模、实时的机器学习技术攻克推荐场景中的个性化与精准度难题，让推荐更懂用户、更贴合真实需求； 4、千亿级数据规模架构：深耕大规模离线计算与分布式系统的性能及调度优化，构建高可用、高吞吐、低延迟的在线推荐服务，稳定支撑海量实时请求； 5、下一代推荐技术体系：融合超大规模机器学习、因果推断、大模型推理等技术，构建业界领先的推荐系统，聚焦推荐全链路的技术探索，实现大模型能力在推荐链路中的高效复用。

1、2027届获得硕士及以上学位，计算机、电子信息、人工智能、机器学习等相关专业； 2、具备扎实的机器学习和深度学习基础，熟悉大语言模型、多模态模型、推荐系统或强化学习中的一个或多个方向； 3、具备以下至少一个领域的研究或实践经验： 1）大模型预训练、后训练、微调与对齐； 2）多模态理解与跨模态表征学习； 3）生成式推荐、序列推荐与用户建模； 4）强化学习与长期价值建模； 5）冷启动、跨域迁移与多目标优化； 4、具备较强的算法设计、实验分析和工程实现能力，能够从实际问题中抽象关键技术问题； 5、对大模型与推荐系统的结合有持续兴趣，具备良好的学习能力和创新意识。

加分项 1、在大模型、多模态、推荐系统或强化学习方向有高水平论文、竞赛、开源项目或工业落地经验； 2、具有大规模推荐、广告、搜索、用户增长或智能触达系统研发经验； 3、具有生成式推荐、推荐基础模型、用户行为大模型或多模态推荐实践经验； 4、能够兼顾技术前瞻性与业务落地，对用户体验、平台生态及长期价值有深入理解。

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