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Open nowPosted 76 days ago

具身智能运动控制算法工程师-深圳

anker-in/campushirecn495 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身智能运动控制算法工程师-深圳anker-in/campushirecn · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. anker-in/campushirecn postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 76 days ago

anker-in/campushirecn median: 1 days open

The posting

你将参与： 1. 研发四足、人形机器人（腿足/机械臂）相关强化学习和模仿学习的运动控制算法，基于 IsaacSim/MuJoCo 等仿真平台搭建大规模并行训练环境，实现动作轨迹跟踪、全身协调控制及力控策略，自适应多种地形环境； 2. 参与 Sim-to-Real 迁移全流程，系统性分析并解决电驱、结构、传感器相关 gap ，结合系统辨识、状态估计、域随机化等技术提升真机部署鲁棒性； 3. 实现运控系统端侧高效部署，与认知大模型、空间/语义感知模型构建分层端到端架构，完成从环境感知、高层决策到底层运动执行的跨模型协同； 4. 对齐 Scaling Law 驱动的运动智能前沿，探索动作基模、世界模型驱动运控、多模态具身大模型等新范式，构建面向通用运动能力的统一架构与训练体系；

1. 2027届毕业生，硕士及以上学历及以上，控制科学、计算机科学、机械电子、机器人等相关专业。 2. 掌握机器人运动学/动力学基础，了解多刚体动力学建模、正逆运动学等核心算法； 3. 具备强化学习理论基础，熟悉 PPO、SAC 等主流算法，有实际项目或课题经验； 4. 熟练使用 Python，熟悉 PyTorch 深度学习框架，具备良好的代码规范和工程能力； 5. 具备至少一种仿真工具（MuJoCo/Isaac Gym/PyBullet/Gazebo）的使用经验； 6. 熟悉 C++ 和 Linux/ROS 开发环境者优先。 加分项 有 Locomotion/Manipulation 运动模型相关研究经验； 有四足/人形机器人真机开发或调试经验（如宇树、云深处等平台）； 在 ICRA/IROS/RSS/CoRL 等顶会或机器人相关期刊发表过论文；

加入我们的理由: 技术前沿：团队正在构建面向量产的运动模型，可直接参与从"单任务策略"到"大小脑统一运动智能"的范式跃迁，而非仅做传统控制算法的工程复现； 全栈闭环：从大规模仿真训练、sim2real 迁移到多台真机（Unitree Go2/B2 及自研平台）实物验证，完整经历算法开发、仿真验证、真机落地的全链路，快速积累产品级运控经验； 成长加速：扁平化技术团队，算法负责人具备多年四足/人形运控经验，与你直接 pair work；鼓励发表顶会论文，优秀者可主导核心模块设计；

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