Job Description
Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.
About The Role
The AI innovation team at Agility works on building and deploying next-generation robot foundation models and end-to-end policies on humanoid robots. Your goal will be to develop and test cutting-edge methods for imitation learning and reinforcement learning on humanoid robots, in order to establish the techniques necessary for humanoid robots to perform different real-world tasks. You will work on a team, running experiments on humanoid robots, and will research and implement methods which can be transferred into production.
About the Work
- 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
About You
- 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
- MS in Robotics, Computer Science, or a related field.
Bonus Points
- 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 modern reinforcement learning techniques for locomotion, manipulation, and whole-body control
- Experience with writing performant, high quality software in C++
This a hybrid position based out of one of
About Agility Robotics
Builder of Digit, a humanoid robot designed for warehouse logistics.
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