Agility Robotics aims to make robots commonplace and approachable by developing advanced humanoid robots like Digit that can work alongside people in various environments. The company is focused on solving engineering challenges and creating next-generation robot foundation models and end-to-end policies to enhance robot mobility, dexterity, intelligence, and efficiency.
Requirements
- 3+ years of experience developing and deploying learning-from-demonstration.
- Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.
- Experience with modern learning-from-demonstration tools like DiffusionPolicy.
- Experience with robot data collection, training, and testing on hardware to perform manipulation tasks.
- Ability to work collaboratively in a fast-paced environment to deliver safe, high-quality software.
- Advanced degree (MS or PhD) in Robotics, Computer Science, or a related field.
- Experience with modern reinforcement learning techniques for locomotion, manipulation, and whole-body control.
Responsibilities
- Design, train, and deploy robust policies for locomotion, manipulation, and dynamic interactions with the environment.
- Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks.
- Design and implement new simulation environments and tasks to support training and deployment of control policies.
- Develop, design, and test imitation learning methods.
- Collaborate with Robotics Software and AI engineering teams to develop policies which can be transferred to production.
Other
- Advanced degree (MS or PhD) in Robotics, Computer Science, or a related field.
- Publications in top ML or robotics conferences (e.g. NeurIPS, ICML, CoRL, RSS, ICRA).
- Familiarity with robot simulation environments (e.g. Mujoco, Isaac Sim) and sim-to-real transfer techniques.
- Experience with writing performant, high quality software in C++.
- Ability to work collaboratively in a fast-paced environment.
