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Open nowPosted 86 days ago

真机强化学习算法工程师

zcnma1sv5kma/index41 open roles

Where
Suzhou, Jiangsu, Chinese Mainland
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Your applicationOpen now真机强化学习算法工程师zcnma1sv5kma/index · Suzhou, Jiangsu, 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.

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 86 days ago

The posting

1.负责面向人形/双足/四足机器人的真机强化学习算法研发,设设计端到端运动控制与操作决策略,实现从仿真到真机(Sim2Real)的高效迁移与持续迭代。 2.搭建大规模真实机器人强化学习训练闭环,负责真机数据采集、策略训练、在线评估与持续学习系统的工程化落地。 3.深入分析真机部署中的硬件特性(电机动力学、通信延迟、传感器噪声、执行器饱和等),构建高保真仿真模型与域随机化策略,缩小仿真-真机差距。 4.开发自动化真机部署与评测工具链,支持多机并行训练、策路快速迭代及A/B测试,提升算法验证效率与复现性。 5.跟踪具身智能与强化学习前沿进展(如VLA后训练、Offline FRL、World Model等),推动前沿技术在真实机器人系统中的创新应用与论文/专利积累。

1.计算机、机器人、自动化、人工智能等相关专业硕士及以上学历,具备扎实的强化学习理论基础与机器人学背景。 2.精通主流深度强化学习算法(PPO、SAC、DDPG等),具备大规模分布式训练经验;熟悉PyTorch,具备优秀的Python/C++工程能力。 3.具有真实机器人(人形/双足/四足/机械臂)强化学习落地经验熟悉Sim2Real迁移中的关键问题(动力学建模、延迟补偿、感知仿真、域随机化等)。 4.熟悉至少一种机器人仿真平台(Isaac Gym/Sim/Lab、MuJoCo、Gazebo等),了解ROS/ROS2系统;具备机器人运动学/动力学建模与控制器设计经验者优先。 5.在CORL、RSS、ICRA、IROS、NeurIPS、ICML等顶会发表过相;关论文,或具有开源项目贡献、RoboMaster/机器人竞赛经验者优先;对技术有极致追求,具备良好的团队协作与沟通能力。

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