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Open nowPosted 113 days ago

多模智能交互算法专家

agirobot/referral515 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now多模智能交互算法专家agirobot/referral · Shanghai, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. agirobot/referral postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 113 days ago

agirobot/referral median: 1 days open

The posting

1. 原生多模态端到端交互系统研发：主导/参与 Any-to-Any / Omni-to-Omni 原生多模态交互大模型的架构设计与核心策略研发。打破级联拼接死锁，在统一网络中实现流式音频、高频 3D 视觉空间特征与语言文本的高维流式对齐，打造视听结合的多模态交互体验。 2. 全双工流式交互体验提升：深度优化流式全双工交互机制，构建高敏捷的流式判停、无感插话、自然打断与拒识算法。攻克全双工并发与自回归解码的顺序死锁，实现百毫秒级语义接管，支持在不阻塞当前全双工业务流的前提下，异步高频调用底层技能。 3. 交互驱动型任务闭环：以全双工交互为核心入口，结合流式多模态感知与Agentic OS ，打通机器人在复杂物理现场中长程任务的自主规划、执行与动态自进化闭环，提升任务完成成功率；构建模糊和突发事件的主动追问澄清，多模态长程任务中的必要人机信息同步，交互模型与底层本体原子技能的高效协同等。 4. 交互沙盒演进系统：负责全双工交互的仿真练兵场(沙盒体系)构建。配合端侧“影子模式”，设计高频多模态异常数据（如长尾卡壳、打断失败片段）的“错误切片大回流”链路，并将其注入仿真沙盒进行千倍速的高烈度对抗；主导建立一套包含全双工流式评测、技能协同评测在内的多模态一致性仿真评测体系，全面加速模型交互智商的自进化。

1. 背景与资历：计算机、人工智能、自动化、声学或相关专业硕士及以上学历；具备 3 年以上（或博士毕业后 2 年以上）在一线科技大厂、头部 AI 研究机构或前沿具身智能企业多模态/语音大模型研发的实际工程落地经验。具备极扎实的深度学习理论基础，深刻理解原生多模态大模型（Speech2Speech / Omni-to-Omni）的序列建模原理、流式架构。 2. 具备极强的编程与工程架构能力，精通 Python，掌握 PyTorch 及主流大模型分布式训练与推理调优工具（如 Megatron-LM、DeepSpeed、vLLM 等），能通过模型、架构、链路调优解决业务痛点。熟练使用AI辅助工作提效，深度使用claude/codex，并有自己见解。 3. 对具身智能有极大的技术热忱，具备卓越的跨团队协作与软硬一体化协同思维 4. 作为核心成员完整参与过国内外主流原生多模态/全双工大模型底层训推、对齐及全双工状态重构者优先。 5. 在 ICML、NeurIPS、ICLR、ICASSP、Interspeech 等国际顶级 AI 或语音学术会议/期刊上以第一作者发表过重磅多模态/全双工交互相关论文，或在知名语音/多模态 AI 竞赛中获得过 Top 名次者优先。

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