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Open nowPosted 215 days ago

模拟器场景任务生成与验证 / 模拟器环境搭建与训练工程师

wcn7iq2vq1am/86371187 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now模拟器场景任务生成与验证 / 模拟器环境搭建与训练工程师wcn7iq2vq1am/863711 · Shanghai, 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. wcn7iq2vq1am/863711 postings stay open a median of 1 days.

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 215 days ago

wcn7iq2vq1am/863711 median: 1 days open

The posting

1. 负责基于 ManiSkill 等仿真平台的场景构建、任务生成与验证，以及 RL 训练环境搭建的完整技术链路。 2. 负责3D资产的接入、处理与系统化验证，包括机器人和物体几何结构、材质属性、关节配置、碰撞体构建、物理参数设定及抓取方式与位姿等等关键环节； 3. 负责机器人操作任务的大规模复杂场景生成与构建，支撑高质量数据规模化生成与任务持续迭代； 4. 负责机器人操作环境的创建与验证，确保任务定义、接触逻辑、可操作性和可执行性在仿真中准确成立； 5. 将仿真环境与 RL、motion planning、数据平台等模块打通，支持场景采样、任务配置、运行调试和问题定位； 6. 支持在模拟器中扩展软体物体与机器人传感器（如tactile）等要素，并参与推进部分 sim2real 对齐工作。

1. 计算机、机器人、自动化、图形学、人工智能等相关专业本科及以上学历，具备扎实的工程实现能力； 2. 熟悉 ManiSkill、SAPIEN、Isaac、MuJoCo 等至少一种机器人仿真平台，具备实际环境开发经验； 3. 熟悉 3D 资产处理与模拟器场景搭建流程，理解 3D资产(asset)、3D场景(scene)、任务(task) 之间的关系，能够独立完成环境构建、验证与调试； 4. 熟悉机器人与场景交互中的碰撞、接触、关节、动力学参数、抓取位姿、任务约束等等关键问题；具备完整的资产、场景与任务验证经验者优先； 5. 能够将仿真环境与 RL 训练流程有效衔接，理解任务交互机制对训练效果的影响；有大规模场景和任务生成、环境搭建、RL、sim2real 经验者优先； 6. 对复杂且具有挑战性的机器人与物体交互任务具备浓厚兴趣或相关经验者优先。

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