Agility's humanoid robots are deployed today in manufacturing, distribution, and logistics. Proven automation for industrial environments. Backed by SoftBank VF.
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.
What they're looking for
- 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
More about this role
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.
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.
- 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...
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