Embodied AI & Robotics Curriculum Engineer

Position Summary

You will create a free online course dedicated to Embodied AI, using the Flexiv physical AI SDK and Flexiv robotic arm.

Responsibilities:
Design a multi-lesson curriculum covering the following technical milestones:
1. Teleoperation & Data Collection: Use a hand-held gripper/glove and SDK to capture high-fidelity manipulation data.
2. Policy Training: Use an open-source physical AI pipeline to train a robotic policy for Flexiv robots.
3. Simulated Environment Setup: Build a high-fidelity digital twin of the training scene within NVIDIA Isaac Sim.
4. Virtual Rollout: Successfully rollout and validate the trained policy within the Isaac Sim environment.
5. Policy Refinement: Use Reinforcement Learning (RL) within simulation to improve model robustness and success rates.
6. Sim-to-Real Transfer: Rollout the refined policy using Flexiv robots for real-world verification.

Requirements:
1. Education: Currently pursuing a MS or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
2. Programming: Strong proficiency in Python and experience with Linux/Ubuntu environments.
3. Simulation: Prior experience with NVIDIA Isaac Sim
4. AI/ML: Understanding of imitation learning, reinforcement learning, and neural network architectures.

Preferred Skills:
1. Teaching/Content Creation: Experience as a Teach Assistant (TA), witing technical blogs, or creating YouTube tutorials.
2. ROS/ROS2: Familiarity with the Robot Operating System (ROS).
3. AI/ML: Experience training and deploying high-level learning-based robotic policies.