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Open nowPosted 224 days ago

仿真算法工程师

agirobot/referral515 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now仿真算法工程师agirobot/referral · Shanghai, Chinese Mainland

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market. agirobot/referral postings stay open a median of 1 days.

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 224 days ago

agirobot/referral median: 1 days open

The posting

1. 职位概览 - 职位使命: 构建高保真物理仿真平台，支撑机器人 manipulation 算法的内部数据闭环生成与模型回归测试，实现"仿真→真机"的高效迁移。 2. 为什么加入我们？ 在具身智能的迭代闭环中，仿真环境是算法进化的加速器。 - 物理级仿真挑战: 你需要构建支持接触-rich manipulation 任务的高保真仿真器，处理碰撞、摩擦、形变等复杂物理现象，让仿真数据具备真机迁移价值。 - 数据闭环核心: 你将打造自动化仿真数据生产线，支持大规模并行数据生成，为 VLA 和 RL 训练提供源源不断的合成数据。 - 回归测试基础设施: 建立模型版本的自动化仿真评测体系，让每一次模型迭代都有可靠的性能基线。 3. 岗位职责 物理仿真系统构建 - 搭建并优化机器人 manipulation 仿真平台，实现高保真物理模拟 - 开发多样化场景与物体资产库，覆盖家居、工业、商超等 manipulation 任务场景 - 缩小Sim2Real Gap，引入域随机化、系统辨识等技术提升迁移效果 仿真数据闭环 - 与研究团队协作，支持在线学习和评测 - 设计自动化仿真数据生成 pipeline，支持批量轨迹采集与自动标注 - 对接真机数据分布，通过仿真生成难以采集的 corner cases 和负样本 - 与数据工程团队协作，将仿真数据无缝接入训练数据湖 模型回归测试平台 - 构建模型版本的自动化仿真评测框架，定义 manipulation 任务的评估指标（成功率、轨迹效率、鲁棒性等） - 实现 CI/CD 集成，支持模型提交后的自动仿真验证与性能报告生成 - 建立仿真-真机性能关联模型，用仿真指标预测真机表现

必备条件 - 扎实的物理仿真功底: 深入理解刚体动力学、接触力学，熟练使用 MuJoCo、Isaac Sim/Gym等至少一种仿真平台 - 机器人学基础: 熟悉运动学、动力学，了解常见机器人本体（机械臂、夹爪、灵巧手）的建模与控制 - 工程能力: 精通 Python/C++，具备大规模并行仿真经验（多 GPU、分布式仿真） - 问题驱动: 对 Sim-to-Real 差距有深刻理解，有实际迁移项目经验 优先条件 - 有机器人 manipulation 仿真项目经验（抓取、放置、装配、操作铰接物体等） - 熟悉域随机化（Domain Randomization）、系统辨识、数字孪生等技术 - 有 RL/VLA 训练经验，理解合成数据在端到端模型训练中的作用 - 在 RSS、CoRL、ICRA、IROS 等机器人顶会有相关产出 5. 加分项 - 有使用世界模型作为仿真器经验 - 参与过开源机器人仿真项目 - 有 GPU 并行计算、CUDA 优化经验 - 熟悉 Blender/USD 等 3D 资产制作流程

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