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Open nowPosted 533 days ago

机器人全栈算法实习生（Robotics Full-Stack Algorithm Engineer）

agirobot/internrecruitment362 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now机器人全栈算法实习生（Robotics Full-Stack Algorithm Engineer）agirobot/internrecruitment · Beijing, Chinese Mainland

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The clock on this job

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11.8% 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. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 533 days ago

The posting

职位名称：

我们正在招聘一位具备系统视野、扎实算法功底与工程能力的机器人全栈算法工程师，加入我们面向真实世界任务的遥操作与智能控制系统研发。该职位将聚焦于探索遥操作在感知、建图、控制、人机协作等方面的潜力，集成多模态输入输出设备，并提升远程操作的效率、自然性与鲁棒性。同时，你将参与构建机器人端的高质量数据采集系统与学习型控制模型，推动视觉语言动作（VLA）等新一代方法在实际任务中的落地表现。

1.设计并实现机器人系统中的关键算法模块，包括但不限于感知（perception）、运动规划（planning）、控制（control）、状态估计（state estimation）、强化学习（reinforcement learning）与操作策略学习（manipulation policy learning）等。 2.独立负责具体任务目标的技术方案制定与交付，快速理解需求、拆解问题，并推动高质量实现。 3.主动识别系统性能瓶颈，提出并验证改进方案，持续优化系统稳定性与效率。 4.与系统工程、硬件集成、仿真测试等团队紧密协作，推动算法模块在真实场景中的有效部署与迭代。

1.对机器人技术充满热情，关注前沿进展，具备持续学习与深入钻研的主动性。 2.具备优秀的理解能力与自主驱动，能够在不确定条件下厘清需求、独立推进任务。 3.精通 C++ 与 Python，具备良好的代码结构设计、工程实现与性能调试能力。 4.对机器人基础算法体系有全面认知，并在以下至少一个方向具有深入经验： • 感知（图像处理、点云理解、多模态融合、SLAM） • 运动规划（采样规划、轨迹优化等） • 控制（位置/速度/力控制，MPC 等） • 状态估计（Kalman / particle filter，传感器融合） • 强化学习与模仿学习（包括行为克隆、DAgger、PPO、Diffusion Policy 等） • 操作策略学习（manipulation policy learning），具备从感知到动作生成的端到端建模能力 • 拥有对机器人系统架构的整体理解，能够快速上手和集成不熟悉的算法模块。 • 欢迎具有强大学习能力和成长潜力的候选人，即使在某些方向经验尚浅，也能迅速适应、持续成长。

加分项： • 有机器人实机部署经验，特别是在高复杂度任务中的经验 • 有机器人系统或远程操控经验 • 在机器人或机器学习顶级会议（ICRA, CoRL, RSS, NeurIPS 等）发表论文者优先 • 熟悉 ROS/ROS2、Mujoco、PyBullet、Isaac Sim 等仿真和开发工具链者优先

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