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 our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Anticipated Salary Range

$166,000—$260,000 USD

In addition to base pay, our competitive total rewards package consists of the following for full-time employees:

401(k) Plan: Includes a 6% company match.
Equity: Company stock options.
Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
Benefit Start Date: Eligible for benefits on your first day of employment.
Well-Being Support: Employee Assistance Program (EAP).

Time Off

Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
Parental Leave: Generous paid parental leave programs.
Work Environment: A culture that supports flexible work arrangements.
Growth Opportunities: Professional development and tuition reimbursement programs.
Relocation Assistance: Provided for eligible roles.
Annual Discretionary Bonus: Provided for eligible roles.

All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.