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Open nowPosted 5 days ago

具身后训练强化学习算法leader

agirobot/index77 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now具身后训练强化学习算法leaderagirobot/index · Shanghai, Chinese Mainland

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 5 days ago

The posting

1. 负责具身基础模型的后训练与强化学习研发，持续提升机器人任务的成功率、执行效率、鲁棒性与泛化能力。 2. 研究如何利用机器人真实执行中的成功、失败、及环境反馈，减少对人工的依赖，推动机器人自主能力提升。 3. 探索机器人经验的数据配方与 Scaling Law，研究交互规模与模型能力增长之间的关系。 4. 构建高效、稳定、可扩展的具身后训练系统。 5. 设计并开展仿真及真机实验，推动算法在实际任务中的验证、迭代与规模化应用。

1. 硕士及以上学历，计算机、人工智能、机器人、自动化等相关专业，具备扎实的数学 / 机器学习 / 强化学习基础，和良好的代码能力。 2. 熟悉强化学习核心算法与原理，对 Offline/Online RL 等方向有深入理解。 3. 具备较强的算法研究与实验能力，能够独立完成问题分析、算法设计、实验验证与结果分析。 4. 具备良好的工程实践能力，熟悉 PyTorch / RLinf 等框架，有大规模模型训练或强化学习实践经验。 加分项 1. 有 VLA / VLM、具身智能、真实机器人强化学习或具身大模型后训练研究经验。 2. 有分布式强化学习、Offline-to-Online RL、Reward / Critic Learning 等相关研究经验。 3. 在高水平会议发表论文，或具有高质量开源项目、算法落地成果。

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