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Open nowPosted 108 days ago

对话智能算法专家

weikezhijia/msxf4 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now对话智能算法专家weikezhijia/msxf · Beijing, Chinese Mainland

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This job: posted 108 days ago

The posting

岗位职责 1. 贷后对话智能分析与复盘系统建设 主导贷后场景下对话分析与复盘算法的设计与落地。基于业务场景定制的ASR语音转文本模型，将座席每日全部通话转化为结构化文本；融合NLP模型与LLM+智能体架构，对通话进行深度语义分析与多维度评估，涵盖沟通流程、客户情绪、异议处理、策略执行、合规表现、成交推进等维度。逐通对话输出优点、待改进点及优化建议，自动总结最值得保持和最需要提升的关键能力，帮助主管从"听录音"升级为"看洞察"，快速完成高质量复盘。 2. 优秀话术挖掘与智能推荐引擎研发 构建优秀话术挖掘与推荐系统。结合案件画像、客户特征、沟通过程等多维特征，从海量历史通话中智能匹配处理效果最佳的相似案例，自动定位关键对话片段，解析优秀座席的话术策略与成功原因，输出可复用的沟通模板与策略建议，帮助新人快速学习、复制优秀经验，实现从"发现问题"到"解决问题"的能力提升闭环。 3. 合规质检与风险防控 基于正则模型+NLP模型+大模型+智能体三模融合架构，构建通话的智能合规质检能力。内置监管规则库，实时检测违规话术并自动标记，对委婉式违规、跨节点复杂对话中的隐性违规进行深度研判，有效降低合规风险。 4. 模型持续优化与业务价值闭环 持续跟踪LLM前沿技术，结合业务反馈数据迭代优化对话分析模型的效果，推动算法从实验室到生产的高效落地与价值闭环。 任职要求 基本条件： 硕士及以上学历，计算机、人工智能、自然语言处理等相关专业，博士优先；5年以上NLP/大模型/文本挖掘算法研发经验 精通Python，熟练使用PyTorch/TensorFlow等深度学习框架，熟悉LangChain等Agent开发框架 深入理解NLP核心算法（意图识别、情感分析、NER、文本摘要、多轮对话管理），有大规模文本数据处理与挖掘经验 熟悉大模型微调技术（SFT、RLHF/DPO）与Prompt工程，有Qwen、ChatGLM、DeepSeek等开源模型调优经验 核心能力要求： 必须具备海量文本数据挖掘与分析经验，能够从非结构化文本中高效提取结构化知识与洞察 有对话分析、智能质检、语音交互、话术推荐等相关项目落地经验（不限行业） 加分项（按优先级排序）： 有贷后管理/资产保全场景的对话分析、智能复盘系统落地经验者优先 有客服/电销场景的对话分析、话术挖掘、智能质检经验者优先 熟悉语音技术栈（ASR、TTS）及语音-文本多模态融合者优先 有顶会论文发表（ACL/EMNLP/AAAI等）或知名大模型应用产品落地经验者优先 特别说明： 纯贷后管理背景的人才稀缺，我们更看重底层NLP与大模型算法能力+海量文本挖掘经验，业务背景可入职后快速补齐。

岗位职责 1. 贷后对话智能分析与复盘系统建设 主导贷后场景下对话分析与复盘算法的设计与落地。基于业务场景定制的ASR语音转文本模型，将座席每日全部通话转化为结构化文本；融合NLP模型与LLM+智能体架构，对通话进行深度语义分析与多维度评估，涵盖沟通流程、客户情绪、异议处理、策略执行、合规表现、成交推进等维度。逐通对话输出优点、待改进点及优化建议，自动总结最值得保持和最需要提升的关键能力，帮助主管从"听录音"升级为"看洞察"，快速完成高质量复盘。 2. 优秀话术挖掘与智能推荐引擎研发 构建优秀话术挖掘与推荐系统。结合案件画像、客户特征、沟通过程等多维特征，从海量历史通话中智能匹配处理效果最佳的相似案例，自动定位关键对话片段，解析优秀座席的话术策略与成功原因，输出可复用的沟通模板与策略建议，帮助新人快速学习、复制优秀经验，实现从"发现问题"到"解决问题"的能力提升闭环。 3. 合规质检与风险防控 基于正则模型+NLP模型+大模型+智能体三模融合架构，构建通话的智能合规质检能力。内置监管规则库，实时检测违规话术并自动标记，对委婉式违规、跨节点复杂对话中的隐性违规进行深度研判，有效降低合规风险。 4. 模型持续优化与业务价值闭环 持续跟踪LLM前沿技术，结合业务反馈数据迭代优化对话分析模型的效果，推动算法从实验室到生产的高效落地与价值闭环。 任职要求 基本条件： 硕士及以上学历，计算机、人工智能、自然语言处理等相关专业，博士优先；5年以上NLP/大模型/文本挖掘算法研发经验 精通Python，熟练使用PyTorch/TensorFlow等深度学习框架，熟悉LangChain等Agent开发框架 深入理解NLP核心算法（意图识别、情感分析、NER、文本摘要、多轮对话管理），有大规模文本数据处理与挖掘经验 熟悉大模型微调技术（SFT、RLHF/DPO）与Prompt工程，有Qwen、ChatGLM、DeepSeek等开源模型调优经验 核心能力要求： 必须具备海量文本数据挖掘与分析经验，能够从非结构化文本中高效提取结构化知识与洞察 有对话分析、智能质检、语音交互、话术推荐等相关项目落地经验（不限行业） 加分项（按优先级排序）： 有贷后管理/资产保全场景的对话分析、智能复盘系统落地经验者优先 有客服/电销场景的对话分析、话术挖掘、智能质检经验者优先 熟悉语音技术栈（ASR、TTS）及语音-文本多模态融合者优先 有顶会论文发表（ACL/EMNLP/AAAI等）或知名大模型应用产品落地经验者优先 特别说明： 纯贷后管理背景的人才稀缺，我们更看重底层NLP与大模型算法能力+海量文本挖掘经验，业务背景可入职后快速补齐。

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