Scale physical intelligence beyond the simulation!
about the company
We represent a hyper-growth deep-tech startup revolutionizing industrial automation through Embodied AI. Build generalizable, intelligent software platforms that control complex physical systems in the real world.
about the role
Bridge the gap between cutting-edge AI research and physical execution by taking models out of simulation and onto real hardware.
- Model Design & Deployment: Develop behavior cloning, neural control, and RL models for robotic mobility and deploy them to physical machines.
- Sim-to-Real Transfer: Analyze real-world telemetry and solve core sim-to-real gap challenges through rapid hardware iteration.
- Scale Infrastructure: Manage multi-sensor data streams and multi-node GPU training workflows for large-scale experiments.
skills and experience
- MSc/PhD in Robotics, AI, or Computer Science with strong research or industry experience (1-2 years)
- Deep fluency in PyTorch, neural control, policy learning, and agent-based training paradigms.
- Proven track record deploying simulation-trained algorithms onto functional robotic hardware.
- Mandarin speaking required as you need to liaise with Chinese counterparts who can only speak and write in Mandarin
- Bonus: Multimodal foundation models (vision/language/kinematics) or top-tier publications (ICRA, IROS, NeurIPS, CVPR)
To apply online please use the 'apply' function, alternatively you may contact Evangeline. (EA: 94C3609/ R24124002)
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