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Open nowPosted 112 days ago

抖音风控基座模型算法工程师（LLM & Agentic AI方向）-Data

ByteDance19,207 open roles

Where
Hangzhou, Zhejiang, Chinese Mainland
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Your applicationOpen now抖音风控基座模型算法工程师（LLM & Agentic AI方向）-DataByteDance · Hangzhou, Zhejiang, 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. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 112 days ago

ByteDance median: 2 days open

The posting

团队介绍：风控算法团队深耕于抖音（短视频、直播、电商、本地生活等）、今日头条等多个字节系业务，涵盖内容、交易、流量、账号等多个场景的底线风险治理、黑灰产对抗及复杂反作弊等关键任务。风控场景具有对抗性极强、逻辑推理链路长及海量多模态数据等挑战。目前，团队正积极推进大语言模型（LLM/MLLM）与 Agentic AI 技术的深入研究与工业化落地。通过探索前沿的模型训练范式、自主规划的 Agent 架构以及严谨的 Harness Engineering 体系，我们致力于打造下一代智能风控基础设施，为十亿级用户的社区生态保驾护航。

1、风控大模型建设：主导风控领域LLM、MLLM、及风险知识图谱等的研发、落地与优化，突破传统风控策略与模型的局限，增强风控强对抗场景下的风险内容感知、理解及识别能力； 2、风控Agent研发：负责风控自主对抗Agent的方案设计、工程化落地，实现风险发现、研判、处置、复盘的全链路智能化升级，提升风控对抗时效，降低运营成本； 3、技术影响力建设：持续跟踪LLM、MLLM、Agent等前沿技术趋势，结合风控业务场景完成技术创新与优化落地；主导技术成果沉淀、对外合作及技术交流，打造团队在风控AI领域的行业影响力。

以下满足其一即可 1、大模型训练方向：深度参与过大模型的Pre-training/CPT/SFT/RLHF/RL等训练环节，有大规模分布式训练与推理加速经验；有多模态大模型（MLLM）经验者优先； 2、Agent系统方向：主导或深度参与过Agent系统的架构设计与落地，熟悉Tool Use、Planning、Memory、Multi-Agent协同等能力，有工业级Agent系统上线经验者优先； 3、结构化数据+LLM方向：有Graph-LLM、行为序列建模、图神经网络（GNN）相关落地经验，熟悉大模型与结构化数据融合的前沿方案； 4、评估与工程体系方向：有构建Benchmark评估体系、模型Harness Engineering、大规模模型服务部署经验，能推动模型能力的规模化验证。

加分项 1、有内容安全、反作弊、风控等对抗性业务场景的实战经验，理解风控业务的对抗性、复杂性； 2、在NeurIPS/ICML/ICLR/ACL/CVPR等顶会发表过相关论文，或在业界有开源项目/技术影响力； 3、具备跨团队协作与技术攻坚能力，敢于挑战现有技术范式，对新技术保持敏锐的判断力。

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