具身智能 / Vla / Wam 算法工程师
Tasks
- Apply Sim2Real transfer and test in real robots
- Build training dataset pipeline
- Clean label and govern trajectory data
- Collect teleoperation and robot data
- Conduct system-level integration and testing
- Connect and debug multistream sensors
- Design robot task evaluation metrics
- Develop embodied intelligence algorithms
- Integrate robot SDK ROS nodes with models
- Optimize inference and deployment performance
- Perform reinforcement learning training
- Reproduce adapt evaluate open source robot models
- Run real robot task benchmarks
- Synchronize and calibrate RGBD IMU and tactile data
- Train fine tune deploy robot foundation models
Perks/Benefits
- N/A
Skills/Tech-stack
C plus plus | Camera Calibration | Coordinate transformations | Data Quality | Data labeling | Data quality monitoring | Diffusion Models | Fine Tuning | Forward Kinematics | Hand-eye calibration | IMU | Inference Optimization | Inverse kinematics | Linux | Machine Learning | Model Fine-tuning | Motion Control | Multimodal Learning | Operating System | Python | Quality monitoring | RGBD | ROS | ROS2 | Reinforcement Learning | Robot Operating | Robot Operating System | Robot dynamics | Sim2real | Trajectory Planning | Ubuntu
Education
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