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Open nowPosted 70 days ago

【27届校招】机器人端到端模型算法工程师

flexivrobotics/97193226 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now【27届校招】机器人端到端模型算法工程师flexivrobotics/971932 · Shanghai, Chinese Mainland

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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 70 days ago

The posting

团队介绍： 我们是一支面向机器人应用落地与规模化量产的具身智能后训练团队，负责将前沿模型能力转化为能够在真实场景中稳定运行、持续创造客户价值的机器人产品。团队以实际业务需求和市场反馈驱动技术迭代，贯通数据采集、模型训练、真机评测、部署优化与量产交付全流程。在这里，研发同学不仅能探索 VLA、模仿学习和强化学习等前沿方向，还能在复杂真实环境中持续打磨技术，通过客户使用效果验证判断、调整方向，最终亲手推动算法从实验走向产品、从技术成果走向规模化价值。

职位描述： 1.参与机器人操作的端到端模型研发（包括但不限于VLA、WAM），协助实现闭环控制能力（抓取、打包等）； 2.在导师指导下，学习并设计模仿学习/后训练训练框架与数据使用策略，协助攻关小尺寸、困难物品、透明/反光等物体和长程任务的操作成功率； 3.协助从遥操（外骨骼/同构主从）真机数据和无本体数据（UMI/Ego）中进行数据筛选、清洗与混合训练策略的实现； 4.参与建立模型摸底与迭代闭环，与算法工程化、端侧推理团队协同，保证模型可评测、可部署、训练-部署精度一致。

1.2027届毕业生，本科及以上学历，CS/AI/机器人相关专业优先； 2.精通PyTorch，熟悉模仿学习/强化学习/扩散去噪/自回归等学习方法的原理，有自主修改网络架构的课题或实习经验； 3.有真实机器人数据驱动模型训练与落地的实习经验，能够分析数据模态、比例和action pattern对端到端策略性能的影响； 4.具备较强工程能力，能独立完成数据pipeline、训练、评测全链路；

加分项： 1.有π0系列、LingBot系列、FastWAM等方法实践经验，熟悉JAX者优先； 2.有遥操数据采集（外骨骼AirExo/vive tracker/VR/主从臂）与真机部署实习经验者优先； 3.有仿真评测、数据回流闭环、模型OTA迭代实习经验者优先； 4.在RSS、CoRL、ICRA、ICLR、IROS等顶会发表过具身操作相关论文者优先； 5.具备多模态（图像、点云、力反馈等）数据处理实习经验者优先； 6.熟悉机器人运动学与动力学，有机械臂实际操作实习经验者优先。

培养与发展规划： 校招生入职即配备资深专业导师，提供技术、工程方法与职业发展的一对一全程指导，并结合个人特点定制清晰成长路径。 你将参与对接真实客户需求、机器人落地场景与量产交付的核心业务任务，完整覆盖从需求分析、方案设计到产品迭代的全流程，在市场反馈中同步提升技术深度、工程能力与业务判断力。 团队鼓励新人主动担当、快速试错、输出技术方案，让优质想法切实落地为产品能力。经过 1-2 年实践培养，能力突出者有机会成长为细分技术方向的负责人或核心骨干，独立牵头关键技术 / 业务模块的规划与迭代，协调资源推动落地并对结果负责，实现从校园新人到技术骨干乃至年轻负责人的快速成长。

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