Littelfuse (NASDAQ: LFUS) is a diversified industrial technology manufacturing company shaping solutions for the safe and efficient transfer of electrical energy. Headquartered in Chicago, Illinois, USA, we serve customers across industrial, transportation, and electronics markets worldwide.
机器人全栈算法实习生（Robotics Full-Stack Algorithm Engineer） 北京、上海 实习 职位描述 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。 职位要求 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 投递...
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