Job Summary
The position focuses on training and deploying VLA models specifically for contact-rich manipulation tasks, while also establishing a data flywheel for autonomous construction robots. Furthermore, the role involves researching and optimizing world models for successful edge deployment on tangible hardware platforms.
Responsibilities
- Train VLA models to enhance contact-rich manipulation capabilities.
- Build and maintain the data flywheel for improving autonomous construction robots.
- Research and refine world models for effective performance on physical hardware.
- Ensure the optimized deployment of machine learning systems on edge devices.
Qualifications
- A Bachelor’s, Master’s, or PhD degree in Computer Science, Robotics, or Machine Learning.
- Experience in implementing and deploying learned systems on physical robotic platforms.
- Proficiency in programming using Python and frameworks like PyTorch.
- Familiarity with robotics middleware, particularly ROS2.
