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Open nowPosted 86 days ago

推荐大模型算法工程师 - 番茄

ByteDance19,258 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now推荐大模型算法工程师 - 番茄ByteDance · Shanghai, 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 23 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.2%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: posted 86 days ago

ByteDance median: 23 days open

The posting

团队介绍：Data-番茄团队，负责字节跳动下番茄小说、红果短剧、番茄畅听、国际化短剧等产品的推荐算法和AI相关工作。我们的工作包括优化业界前沿的大规模推荐系统，探索LLM与推荐的结合，并落地生成式推荐范式，从小说、短剧、音频、音乐等内容方向建设完整的内容生态和AI能力，保持业务规模保持超高速增长。

1、推荐大模型在LLM的启发下，在近一年有了长足的发展；番茄依托字节跳动的先进中台，在推荐大模型（LRM）、生成式推荐（GR）领域已有多代方案落地；随着LLM和硬件算力的进一步发展，该方向空间仍有巨大空间；团队将继续紧跟前沿，在LRM、GR和LLM4Rec三大方向全面发力，推动推荐系统的持续进化； 2、LRM；设计并探索Scale上限更高，ROI更好的结构，紧跟LLM超长上下文前沿，推动推荐场景的高效长序列压缩与建模，研究粗精一体LRM进一步释放Scale空间等； 3、生成式推荐；探索番茄多场景多体裁的最佳tokenize方案，研究推荐场景下Reward Model与生成推荐模型的RL后训练，完成生成式模型对部分场景传统推荐模型的替换； 4、LLM4Rec；包括研究如何将LLM的推理能力融入到推荐排序模型，以及完全基于LLM的交互推荐研究。

1、2027届获得本科及以上学历，人工智能、计算机、数学相关专业者优先； 2、对推荐大模型技术有浓厚兴趣，紧跟行业前沿发展； 3、具有扎实的机器学习基础和编码能力，熟练掌握主要的算法和数据结构； 4、在搜索广告推荐大模型领域，有实习或者实践过关键项目的优先； 5、在国际顶级会议发表论文者优先，包括但不限于KDD、SIGIR、RecSys、ACL、NeurIPS等；有推荐大模型相关论文者优先； 6、具备良好的沟通协作能力，能够与团队共同探索新技术，推动新技术在业务落地。

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