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Open nowPosted 79 days ago

抖音AI搜索算法工程师 - 搜索

ByteDance19,261 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now抖音AI搜索算法工程师 - 搜索ByteDance · 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 27 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 79 days ago

ByteDance median: 27 days open

The posting

团队介绍：字节跳动搜索团队主要负责抖音、今日头条、红果短剧、番茄小说、AI搜索等产品以及电商、生活服务等业务的搜索算法创新和架构研发工作。 我们使用前沿的机器学习/大模型技术进行端到端建模并不断创新突破，同时专注于分布式系统、机器学习系统的构建和性能优化，从内存、Disk等优化到索引压缩、召回、排序等算法的探索，致力于支撑字节跳动持续多元化的产品创新和高速的业务增长、基于大模型革新和重塑下一代搜索技术体系，充分给同学们提供成长自我的机会。 主要工作方向包括： 1、探索前沿的NLP技术：全面基于LLM的Query分析、相关性、个性化预估、满意度评估、生成式检索等，全链路应用LLM/VLM，每个细节都充满挑战； 2、跨模态匹配技术：进行多模态预训练，在超大规模的多模态表征、匹配、生成等多个技术方向上持续突破，打造世界领先的多模态搜索系统； 3、大规模流式机器学习技术：应用大规模机器学习，解决搜索中的推荐问题，让搜索更加个性化更加懂你； 4、千亿级数据规模的架构：从大规模离线计算，分布式系统的性能、调度优化，到构建高可用、高吞吐和低延迟的在线服务的方方面面都有深入研究和创新； 5、推荐技术：基于超大规模机器学习、因果推断、大模型推理等技术手段，构建业界领先的搜索推荐系统，对搜索推荐技术进行探索和创新； 6、AI搜索技术：基于大模型(LLM/VLM)探索多轮、交互式等大模型原生的搜索产品体验。

1、探索大模型和搜索结合的创新技术：随着大模型技术的快速发展，智能搜索领域迎来了新的机遇和挑战，传统搜索技术在面对海量数据、多模态信息以及用户复杂需求时，逐渐暴露出模型容量不足、语义理解能力有限、资源利用率低等问题，基于大模型的智能搜索构建旨在通过引入大模型技术，提升搜索系统的智能化水平，优化用户体验，并解决超大规模检索、复杂语义理解、资源高效利用等核心问题，具体目标包括：探索大模型与排序算法的结合，提升个性化排序的精度和用户体验；研究生成式检索算法，解决百亿乃至千亿级别候选库的超大规模检索问题；利用大语言模型（LLM）提升复杂多义Query的搜索满意度； 2、参与搜索引擎研发，探索提升搜索全链路（分析、召回、粗排、精排、混排）的个性化行为建模、相关性能力提升，包括CTR、CVR预估、向量召回、价值混排、RAG、NLP、LLM、多模态、机器学习、深度学习等，推动搜索算法的落地与能力提升，提升转化效率、用户体验和供给生态； 3、深入参与搜索产品的需求设计，负责算法和工程的高质量交付，持续优化效果提升产品体验； 4、挖掘数据，构建Query理解、召回、排序等模型，提升搜索算法能力； 5、学习前沿技术，探索大模型等创新技术在AI搜索场景的落地。

1、2027届获得硕士及以上学位，人工智能、计算机、电子、自动化、软件工程、数学等相关专业优先； 2、具备扎实的编码能力、数据结构和基础算法功底，熟练运用各种算法框架与工程框架，熟练使用C/C++和Python语言； 3、在搜索、推荐、广告、自然语言处理NLP、自然语言理解NLU、多模态、机器学习、深度学习等一个或多个领域有较深入的研究者优先； 4、在人工智能领域、机器学习领域国际会议或期刊发表论文者优先； 5、具有良好的问题分析解决能力，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、具有基础算法、扎实的机器学习/深度学习基础，熟悉NLP、RL、ML等领域的技术，在KDD、SIGIR、ICML、ACL、COML、EMNLP、CVPR、ECCV、ICCV、NeurIPS、ICLR、SIGGRAPH或SIGGRAPH Asia等顶级会议/期刊上发表论文者优先； 2、ACM/ICPC、NOI/IOI、Top Coder、Kaggle等比赛获奖者优先； 3、在LLM、多模态、大模型、基础模型、世界模型、RL等领域，主导过大影响力项目者优先； 4、具有大规模搜索引擎、推荐系统、分布式系统、计算广告、超大规模数据计算等相关经验者优先。

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