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Open nowPosted 190 days ago

广告场景下的生成式搜广推大模型技术研究-国际化搜索广告(北京/上海/杭州)

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now广告场景下的生成式搜广推大模型技术研究-国际化搜索广告(北京/上海/杭州)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. 4.2%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 190 days ago

ByteDance median: 27 days open

The posting

团队介绍:国际化搜索广告团队不断突破通用搜索引擎变现的界限,覆盖海外应用,致力于构建全球领先的搜索广告变现系统。在国际化搜索广告团队,您将有机会从事大规模分布式存储和架构、自然语言处理、排序和信息检索相关的问题。您还将深入参与我们的广告样式、创意展示和广告投放链路的创新和优化。我们正在寻找勇于挑战困难、热衷于解决复杂问题并与热情洋溢的候选人们共同发展我们的搜索广告产品。

课题介绍: 本课题深耕TikTok全球化广告核心场景,聚焦生成式搜广推前沿技术创新与落地,深度融合大模型与广告业务,攻坚推荐大模型(Large Recommender Model)、大语言模型(LLM)领域的核心技术难题,打造具备自主决策能力的下一代智能广告引擎。 我们布局推荐大模型Scaling Law、端到端统一建模、基于多模态Semantic ID的用户行为序列统一建模、生成式全链路技术(生成式召回、生成式排序、AIGC素材生成、生成式出价)、广告投放智能Agent、超长序列建模、因果推断等前沿方向,应对千亿级特征、毫秒级响应的极致挑战,推动广告推荐向 Foundation Model 范式演进,实现变现效率与用户体验的双向跃升。

课题挑战: 1、探索推荐广告大模型Scaling Law,构建多模态语义统一建模的基础模型; 2、构建面向用户长期价值(LTV)和长周期ROAS的智能广告投放系统,实现商业价值与用户体验的双向平衡了; 3、优化大模型全流程训练与在线推理框架,平衡算力成本与实时响应性能,破解效果-延迟的落地瓶颈。

课题价值: 突破原有技术瓶颈,推动广告系统从“匹配”向“生成与推理”范式升级,提升全链路ROI、泛化性与决策智能化,沉淀行业领先技术壁垒,提升用户体验和商业价值。

1、2027届毕业,获得博士学位,人工智能、计算机、自然语言处理、计算机视觉等相关专业优先; 2、在人工智能领域顶级会议上有发表论文或有深入研究经历者优先; 3、优秀的编码能力,熟悉C++和Python,扎实的数据结构和算法功底,出色的数据和问题分析能力; 4、有深度学习实战经验,有机器学习算法优化理论的研究经验,有大模型/搜索/推荐/广告相关领域经验; 5、良好的沟通协作能力,对技术有执着的追求和热爱,敢于突破,能和团队一起探索新技术,推进技术进步。

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