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Open nowPosted 292 days ago

多模态人机交互算法工程师/研究员

xiaopeng/index1,587 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now多模态人机交互算法工程师/研究员xiaopeng/index · Shenzhen, Guangdong, Chinese Mainland
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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. xiaopeng/index 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 292 days ago

xiaopeng/index median: 1 days open

The posting

本岗位重点负责多模态人机交互中的动作与行为生成方向,面向通用人形机器人打造自然、实时且满足物理约束的表情、注视、手势、姿态及全身动作。 1、负责动作生成方向的技术方案与模型架构设计,结合语音、文本、视觉等条件,攻关跨模态对齐、时序建模与可控生成; 2、主导基于 Diffusion Transformer、自回归模型或其他生成式架构的核心算法研发,持续提升动作自然度、语义一致性、多样性和实时性; 3、建立覆盖数据采集、清洗、标注、训练和评测的闭环,设计动作质量、时序同步、稳定性及响应时延等核心指标; 4、推动生成模型与运动控制系统协同设计,将运动学、动力学及安全约束融入训练与推理,完成从仿真到真实机器人的系统验证; 5、承担关键技术攻坚和工程化落地,协同感知、控制、硬件及产品团队解决复杂场景下的鲁棒性、泛化与性能问题,并推动方案持续迭代。

1、计算机、人工智能、自动化、机器人等相关专业,硕士及以上学历;具备突出研究成果或丰富工程经验者可放宽学历要求; 2、具备 5 年及以上动作生成、多模态学习、人机交互或具身智能相关研发经验,主导或深度负责过至少一个从算法研发到系统落地的完整项目;具备突出研究成果或同等能力者可适当放宽年限要求; 3、深入理解 Transformer、Diffusion、VAE 等生成式模型及序列建模方法,具备模型架构设计、训练调优和效果评测经验; 4、熟悉人体动作建模、人形机器人运动学或动力学,能够从动作质量、物理可行性和机器人安全性等维度系统解决问题; 5、熟练掌握 Python、PyTorch,熟悉 C++,具备良好的工程架构、性能分析和问题定位能力; 6、算法工程师方向重点考察模型训练、系统工程、性能优化及真实机器人落地能力;研究员方向重点考察原创算法、研究深度以及论文、专利或开源成果; 7、具备较强的技术判断力、问题拆解能力和结果意识,能够独立推动复杂项目并高效协同算法、控制、硬件及产品团队。 加分项 - 在手势生成、Any-to-Motion、动作重定向或世界模型等方向有深入研究和落地经验; - 具备真实机器人部署、ROS/ROS 2、仿真平台或运动控制系统联调经验; - 具备大规模分布式训练、端侧部署经验,或有代表性的论文、开源项目及专利成果。

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