Tech Stack

Description

You will design and deploy algorithms for dexterous manipulation tasks, developing motion planning models for dynamic environments and deploying them as production-ready solutions on RoboForce robots. Expect to enhance contact-rich robot learning stacks through physics-based simulation.

Requirements

• Master's degree in ML, Robotics, or related field with 4+ years experience or PhD
• Understanding of multimodal models, modern ML architectures
• Expertise in imitation learning, reinforcement learning, tactile sensing, robotics learning
• Proficiency with physical simulators (MuJoCo, IsaacSim, Drake, etc.)
• Proficiency in Python, and deep learning frameworks (PyTorch, JAX)

Responsibilities

• Design and deploy algorithms for dexterous manipulation tasks
• Develop motion planning models for dynamic environments
• Deploy models as production-ready solutions on RoboForce robots
• Create and enhance contact-rich robot learning stacks through physics-based simulation