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Open nowPosted 11 days ago

具身智能研究员／算法工程师——机器人自主进化（Embodied RSI）

shengshu/index98 open roles

Where
Beijing, Chinese Mainland
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Your applicationOpen now具身智能研究员／算法工程师——机器人自主进化（Embodied RSI）shengshu/index · Beijing, 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. shengshu/index 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 11 days ago

shengshu/index median: 1 days open

The posting

我们探索能够从交互经验中持续学习、自主改进的机器人系统，让机器人通过探索、反馈与练习，不断提升技能、策略和解决新任务的能力。

岗位职责 1、研究具身智能的递归自我改进方法，构建“自主探索—执行反馈—失败诊断—能力更新—评估验证”的持续学习闭环； 2、开发基于 LLM／VLM 的机器人 Agent，结合代码生成、工具调用、分层规划与 VLA 策略，实现复杂操作和失败恢复； 3、研究技能自动发现、组合与复用，以及长期记忆和执行系统的持续优化，推动经验跨任务、跨场景积累与迁移； 4、利用仿真、真实机器人交互及人类反馈，开展自动数据生成、策略后训练或世界模型辅助学习； 5、建立可复现的评测流程，验证多轮迭代中的成功率、泛化能力、交互成本与已有能力保持情况。

1、具备计算机、人工智能、机器人或相关专业背景，有扎实的机器学习与编程基础，熟练使用 Python； 2、在以下至少一个方向有深入研究或项目经验：具身 Agent、机器人学习、VLA、强化学习、持续学习、自动程序生成与优化； 3、能独立完成论文复现、系统实现、实验设计与问题分析，重视可验证的能力提升； 4、熟悉机器人感知、运动规划、控制或仿真中的至少一个环节，能够参与搭建完整的交互与评估系统； 5、加分项： a）有真实机械臂、双臂或移动操作平台的部署与调试经验； b）有自进化 Agent、技能库、长期记忆、自动评估或代码搜索经验； c）有 VLA 后训练、失败恢复、人类干预学习、世界模型或 sim-to-real 经验； d）在机器人或机器学习相关会议发表论文，或有高质量开源项目。

相关研究参考 EmbodiedRSI、ASPIRE、RATs、PhysicalRSI、Harness VLA、RoboFoundry、EmbodiRSI、SEES 等。欢迎具备相关能力、希望探索机器人自主学习的候选人。

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