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Open nowPosted 191 days ago

大模型赋能交易与商业场景的技术创新及落地实践研究（北京/上海） - 中国交易与广告

ByteDance19,260 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now大模型赋能交易与商业场景的技术创新及落地实践研究（北京/上海） - 中国交易与广告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 191 days ago

ByteDance median: 27 days open

The posting

团队介绍：中国交易与广告，基于个性化推荐、深度学习和大模型技术，依托抖音、今日头条、红果短剧、西瓜视频、番茄小说等多元产品，构建抖音电商、生活服务、广告营销等核心营收业务的算法策略和工程架构。部门运用领先的算法能力，精准连接海量用户与商家，通过推荐、广告和搜索算法精准匹配需求并促进交易达成，保障用户体验与商家权益，实现营收业务可持续增长；基于深厚的技术积累，构建高效、智能、可靠的交易与广告产品，全面提升多行业收入变现与市场占有。在这里，你将直面超大规模流量与复杂业务场景的技术挑战，深度应用业界领先的商业模型与算法技术，投身面向未来的数字营销能力建设，持续探索前沿技术。

课题介绍： 本课题立足中国交易与广告等商业场景，以大型语言模型（LLM）、视觉语言模型（VLM）、智能体（Agent）、强化学习、多模态生成等前沿技术为核心支撑，重点聚焦搜索、广告、推荐、电商、生活服务、广告营销、内容生产等关键业务场景，针对性破解传统技术体系存在的瓶颈问题。课题的核心研究目标为：借鉴大模型规模法则（Scaling Law）与生成式人工智能技术思路，深入探索技术与商业业务的深度融合路径，构建适配各垂直商业场景的智能模型及系统架构。同时，着力解决技术落地过程中的效率优化、场景适配、合规管控等关键问题，助力业务规模增长、运营效能提升与用户体验优化，推动商业场景数字化、智能化转型进程。

课题挑战： 1、技术适配性：通用LLM与MLLM在垂直商业交易场景存在领域知识薄弱、工具调用不足、语义对齐偏差等问题，需突破多模态协同、时空建模、低标注学习及搜广推融合技术； 2、效率与性能：大模型时延高、耗算力、吞吐低，难以满足高并发低延迟交易与搜广推需求，需通过轻量化、量化、分布式推理等优化性能与成本； 3、决策与规划：复杂商业决策对长周期建模、多目标优化、自适应要求高，AIGC与Agent易产生幻觉、决策偏差与因果缺失，需强化可信推理与风险约束； 4、落地与合规：需解决系统集成、数据质量、内容可控、隐私安全与监管合规问题，保障大模型规模化稳定、安全、合规落地。

课题价值： 1、理论价值：探索大模型在多商业场景的Scaling Law可行性，完善推荐大模型、Agent决策、多模态融合等技术体系，丰富AI在商业领域的应用理论； 2、实践价值：破解各商业场景核心痛点，如提升推荐转化、广告ROI、内容生产效率、客服质量等；降低人工成本，实现商业流程自动化；推动搜广推、电商、广告等领域的技术范式革新，支撑业务规模化增长，同时优化用户体验与商家服务能力，构建可持续的商业生态。

1、2027届毕业，获得博士学位，计算机/数学/信号处理等相关专业优先； 2、对工业场景实际问题感兴趣，具备问题抽象、拆解、研究与方案探索能力，有技术热情； 3、至少在以下一个方向有扎实基础：序列建模、强化学习、大模型后训练、复杂系统或Benchmark设计； 4、代码能力优秀，掌握Python/C++至少一种，熟悉TensorFlow/PyTorch，熟悉Spark/Flink； 5、深入理解PPO、SAC等强化学习核心算法，并有一定项目落地经验优先。

加分项 1、有计算广告、竞价机制相关研究经验的同学优先； 2、在LLM/广告/推荐/NLP/CV等领域有业界经验的同学优先； 3、有顶会论文发表的同学优先（NeurIPS、ICML、ICLR、CVPR、ICCV、ACL、KDD等）； 4、有编程/AI比赛获奖同学优先（ACM/ICPC、NOI/IOI、Top Coder、Kaggle、Codeforces2000+）。

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