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Open nowPosted 78 days ago

【2027 届校招】大小脑融合算法工程师

nwd4iy9rd2s/campusofspiritai57 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now【2027 届校招】大小脑融合算法工程师nwd4iy9rd2s/campusofspiritai · Beijing, Chinese Mainland

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12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 78 days ago

The posting

我们致力于推动数据采集、VLA模型与机器人运控的协同演进。你将不止停留于VLA模型相关的工作，而是同时构建跨机器人与人工智能领域的全栈算法能力与工程实践能力，从整个具身智能系统的角度解决问题。具体方向包括： 1.多模态 VLA 与触觉/力觉融合研发 负责具身多模态大模型及相关算法研发，探索触觉（Tactile）、力/力矩（Force/Torque）等连续传感数据的表征学习、特征提取与 Token 化设计；实现力觉、视觉、语言等多模态信息在 VLA 架构中的深度融合，支撑机器人感知—决策—执行闭环控制。 2.多源具身数据联合训练与数据标准探索 深入调研并主导类 UMI 采集数据与真实机器人端到端交互数据的联合训练（Co-training）机制，设计高效的混合训练策略；参与定义面向 VLA 与运动控制协同的数据表示、数据质量与数据接口标准。 3.跨形态数据对齐与真机泛化 面向不同采集形态和机器人平台的数据分布差异，设计并优化跨形态数据对齐（Cross-embodiment Alignment）、特征对齐及域适应（Domain Adaptation）算法；缩小 UMI 演示数据与真机物理交互数据之间的 Domain Gap，提升模型在真实机器人上的泛化能力与复杂操作成功率。 4.移动操作中的大小脑协同架构研发 探索底盘移动与机械臂操作协同的端到端框架，设计支持全身控制（WBC, Whole-Body Control）的统一架构；推动高层 VLA 策略输出与底层运动控制、动力学解算之间的有效衔接，解决高低频控制的解耦、协同与平滑过渡问题，实现稳定、高精度的移动操作能力。

1.专业背景 计算机、机器人、自动化、人工智能或相关专业硕士及以上学历，具备扎实的数学基础、逻辑思维与问题分析能力。 2.工程与代码能力 熟悉 Python/C++、Linux、ROS/ROS2 等机器人常用工程栈；熟练使用 PyTorch、TensorFlow 等深度学习框架；善于使用 AI 辅助编程工具，具备较强的算法实现、调试和迭代能力。 3.算法与机器人基础 在机器人操作（Robot Manipulation）方向具备深入研究或项目实践经验；具备较扎实的机器学习、深度学习及机器人学基础，对感知、规划、控制或真机系统中的一个或多个方向有实践积累。 4.加分项 有具身智能、VLA、多模态学习、模仿学习、强化学习、运动控制或全身控制相关研究/项目经历； 有真实机器人操作、移动操作或多传感器数据采集与处理经验； 有高质量论文、开源项目或竞赛成果； 对具身智能有强烈热情，愿意深入接触真机，了解底层原理

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