Imitation Learning Algorithm x 3 Vacancies
15~20K 人民币/每月
全职
3~5年
刷新于 8 个月前
89 查看
13 申请
深圳
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工作职责
Our Mission for You:
1. Your core mission is to bridge the digital and physical by teaching robots through imitation. You'll be the driving force behind creating robots that can learn and perform complex -tasks with the fine motor skills of a human.
2. Innovate & Build: Design novel imitation learning algorithms and see them through to real-world deployment, tackling the challenges of real-time performance and precision.
3. Master Bimanual Dexterity: Develop the complete software stack for our two-arm robot imitation learning system, from data to deployment.
4. Explore the Future: Keep us ahead of the curve by researching emerging tech and finding ways to apply the state-of-the-art to solve real problems.
职位要求
We're Looking For Someone Who:
1. Holds a Master's or PhD degree in Computer Science, Electronics, Robotics, or a related field, with at least 3 years of relevant research or industry experience.
2. Possesses deep expertise in imitation learning and/or reinforcement learning, with a proven ability to develop and deploy algorithms on real-world robotic systems.
3. Is highly proficient in Python and has extensive experience with deep learning frameworks such as PyTorch or TensorFlow.
4. Has a strong foundation in robotics fundamentals (kinematics, dynamics, control) and is familiar with the Transformer architecture and multimodal learning. Experience with large language/models is a significant plus.
5. Thrives on turning research into reality, with a track record of building end-to-end robotic solutions.
Bonus Points For:
6. Hands-on experience with :
(1). State-of-the-art algorithms like ACT, MT-ACT, RT-1/RT-2, or Diffusion Policy.
(2). Familiarity with multimodal embodied AI models such as PaLM-E or RT-X.
(3). A history of publications in top-tier robotics, computer vision, or AI conferences (e.g., RSS, CoRL, CVPR, ICRA, IROS, NeurIPS) or distinguished awards in academic competitions.
(4). Practical project experience in robot control and algorithm development.
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