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Open nowPosted 163 days ago

蔚来AGI超星计划-面向销售的Agentic强化学习研究

nio/campus869 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now蔚来AGI超星计划-面向销售的Agentic强化学习研究nio/campus · Shanghai, 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. nio/campus postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.5%14 days
  5. 35.5%30 days
  6. 45.1%60 days
This job: posted 163 days ago

nio/campus median: 1 days open

The posting

课题介绍 本课题聚焦面向销售场景的大模型能力提升，开展系统性的算法研究与训练范式探索。 通过结合 SFT（监督微调）+ RL（强化学习）+ Agentic RL（基于任务驱动的强化学习） 等多阶段训练方法，构建适用于销售垂类的大模型优化路径，重点提升模型在复杂业务场景下的决策能力与执行效果。 在既有基础模型能力之上，目标实现对标行业Top模型的效果突破，整体性能提升约 10%+，并在关键业务指标上形成可量化收益。 预期产出 1. 一套可持续优化的“在线蒸馏 + 强化学习”训练范式 - 构建从数据生成 → 在线蒸馏 → 强化学习闭环优化的完整体系 - 支持模型能力的持续迭代与自我进化 - 适配销售场景中长程、多策略决策的任务特征 2. 一个自研销售垂类大模型及其效果基线 - 形成具备明确指标体系的模型参数版本 - 在核心任务（如洞察建议、话术生成等）上达到可落地水平 - 支持业务侧验证与规模化应用

  • 精通深度学习原理，对Transformer、大语言模型有扎实的理论基础和实践经验；
  • 强大的系统性思维与问题定义能力；
  • 精通并有主流大模型的相关训练和使用工作经验，深入了解主流Agent框架和应用；
  • （加分）在国内外顶尖实验室或者模型团队经历；
  • （加分）重度使用claude、cursor、codex等相关AI工具开发者优先；
  • 学历：硕士及以上在读；
  • 实习时长：6个月以上。
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