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Open nowPosted 187 days ago

灵巧手强化学习工程师(R10986)

agirobot/socialrecruitment476 open roles

Where
Shanghai, Chinese Mainland
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Your applicationOpen now灵巧手强化学习工程师(R10986)agirobot/socialrecruitment · Shanghai, Chinese Mainland

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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

  4. CV RocketApplied on agirobot/socialrecruitment's own form.

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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. agirobot/socialrecruitment 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. 57.8%60 days
This job: posted 187 days ago

agirobot/socialrecruitment median: 1 days open

The posting

一、岗位定位 聚焦灵巧手操作场景，负责从离线模仿到在线强化学习的后训练算法研发，推动从仿真到真机的完整迭代闭环。 二、岗位职责 1. 负责灵巧手操作任务的强化学习算法设计与优化，覆盖从仿真到真机的全流程迭代 2. 研究多模态感知信息（视觉、触觉、力反馈等）与强化学习决策的结合方法 3. 探索将大模型能力与强化学习相结合的技术方案，提升操作精细度与泛化能力 4. 跟踪具身智能与强化学习领域前沿技术，推动算法在真实灵巧手平台持续落地 三、职位要求 1. 基本要求：硕士及以上学历，计算机、人工智能、机器人、控制工程等相关专业；2年以上强化学习或机器人算法研发经验（含博士期间研究） 2. 技能要求：扎实的强化学习理论基础，熟悉主流策略优化算法 精通Python/PyTorch，具备在真实机器人上进行算法部署和调试的项目经验；了解机器人运动学、感知标定等基本知识，能与硬件团队顺畅协作 3. 加分项：有灵巧手或多指操作的真机强化学习经验；有大规模并行仿真与Sim-to-Real迁移经验；在机器人或机器学习顶级学术会议发表过相关论文

承担主要目标/关键任务 开发基于真机强化学习的后训练链路，支持大模型、demo开发、落地POC项目等

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