AI Research Engineer
US$195,000 – US$304,000 / yr base salary
Posted 2 Jul 2026
Advertised as “Senior AI Research Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 3+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
- Visa sponsorship
- Not offered
| Base salary | US$195,000 – US$304,000 / yr |
|---|
Field of studyComputer Science, Robotics (or related)
Study levelMaster's
Field of studyComputer Science, Robotics (or related)
Study levelDoctorate
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++