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Open nowPosted 222 days ago

机器人强化学习应用工程师

f0exxg5fp6u/42612215 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now机器人强化学习应用工程师f0exxg5fp6u/426122 · Shenzhen, Guangdong, 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.

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. 57.8%60 days
This job: posted 222 days ago

The posting

岗位职责 1. 负责机器人强化学习模型的训练、调参与优化，提高策略稳定性与运动表现。 2. 在仿真环境中进行大量实验，调整奖励函数、观测空间、训练参数等关键因素，持续迭代策略效果。 3. 将训练得到的策略模型部署到真实机器人系统中，完成策略验证与调试。 4. 分析仿真与真实机器人运行表现，定位问题并推动策略优化与 sim-to-real 适配。 5. 整理训练流程、实验数据与部署经验，形成规范化训练与应用流程。

1. 熟练使用 Python，c++，能够阅读和理解强化学习或机器人控制相关代码。 2. 了解强化学习基本原理（如 PPO 等策略梯度算法）或机器人运动控制基础。 3. 有仿真训练经验（Isaac Gym / Mujoco / Isaac Sim / RL 框架等）者优先。 4. 具备较强实验能力与问题分析能力，能够进行系统化调参与效果验证。 5. 对机器人运动控制、强化学习或具身智能方向有浓厚兴趣，愿意深入实践与优化

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