Senior AI Software Engineer, Reinforcement Learning

Agility Robotics; Pittsburgh (Allegheny County); Hybrid; USD 187,000 - 292,000; Full time

Benefits offered by this job

401(k) match

Equity options

Medical/dental/vision insurance

Relocation assistance

Parental leave

Flexible work arrangements

Tuition reimbursement

Annual bonus

Job summary

Agility Robotics seeks an AI Controls Engineer to develop, train, and deploy high‑rate reinforcement learning policies for the Digit humanoid platform. You will enable robust locomotion, manipulation, and safe interaction in dynamic environments, integrating perception to achieve perceptive motion in production facilities.

You will work with a team across simulation, on‑robot software, and deployment to ship policies to Digit.

Qualifications

• 4+ years of experience developing and deploying RL policies for robotics.
• Strong Python and PyTorch skills with real‑world robotics focus.
• Experience designing reward functions, tuning hyperparameters, and exploration strategies.
• Experience with perception‑in‑the‑loop control and real‑time sensory inputs.
• Proven ability to deploy RL policies on real robots and in production.

Responsibilities

• Design, train, and deploy robust RL policies for locomotion, manipulation, and whole‑body control.
• Integrate perception into RL policies for obstacle‑aware, collision‑free motion.
• Develop and maintain scalable RL training pipelines and evaluation frameworks.
• Create new simulation environments and tasks to support policy training.
• Collaborate with on‑robot software and deployment teams to ship production‑quality policies.

Skills

Python

PyTorch

RL policies

Perception in‑loop

Robotics deployment

Team collaboration

Education

MS or PhD in Robotics/CS

Tools

Mujoco‑Warp

Isaac

Job description

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.

Agility is a pioneer. Our robot, Digit, is the first to be sold into workplaces across the globe. Our team is differentiated by its expertise in imagining, engineering, and delivering robots with advanced mobility, dexterity, intelligence, and efficiency -- robots specifically designed to work alongside people, in spaces built for people. Every day, we break through engineering challenges and invent new solutions and capabilities that will one day make robots commonplace and approachable. This work is our passion and our responsibility: our mission is to make businesses more productive and people's lives more fulfilling.

Why Join Now

Digit is one of the only humanoid robots deployed in real customer facilities today—at Schaeffler, GXO, Toyota Motor Manufacturing Canada, and Mercado Libre, with 65,000+ hours of real-world operation logged. In June 2026 we announced plans to become the first pure-play humanoid robotics company to trade publicly (ticker AGLT), in a ~$2.5B merger backed by NVIDIA, Amazon, SoftBank Vision Fund 2, and Foxconn. With $300M+ in orders for Digit and a factory built for 10,000 robots a year, we're scaling fast—and the policies you build will ship to robots working alongside people in production, not sit in simulation.

About The Role

The AI Controls team builds high-rate learned controllers that let Digit move robustly, efficiently, and safely in dynamic environments. As an AI Controls Engineer, you'll develop and deploy reinforcement learning policies across humanoid locomotion, whole-body control, and manipulation—integrating perception to enable collision-free, perceptive motion in the real world.

About The Work

• Design, train, and deploy robust RL policies for locomotion, manipulation, whole body control, and dynamic interactions with the environment.
• Integrate perception into RL policies to achieve obstacle-aware, collision-free motion, and perceptive manipulation.
• Develop and maintain core RL infrastructure, including scalable training pipelines and evaluation frameworks.
• Design and implement new simulation environments and tasks to support training and evaluation of control policies.
• Collaborate with on-robot software and deployment teams to ship production-quality policies to Digit.

About You

• 4+ years of experience developing and deploying RL policies for robotics applications.
• Strong Python skills and hands‑on experience with a deep learning framework such as PyTorch.
• Experience designing reward functions, tuning hyperparameters, and implementing exploration strategies to solve complex control tasks.
• Experience with perception‑in‑the‑loop control, integrating real‑time sensory inputs for reactive or adaptive behaviors.
• Proven experience deploying reinforcement learning policies on real‑world bipedal or quadrupedal robots.
• Familiarity with robot simulation environments (e.g. Mujoco‑Warp, Isaac) and sim‑to‑real transfer.
• A collaborative approach and the ability to deliver safe, high‑quality software in a fast‑paced environment.

Bonus Qualifications

• Advanced degree (MS or PhD) in Robotics, Computer Science, or a related field.
• Experience with contact‑rich manipulation, including force‑torque or tactile sensing.
• Familiarity with policy distillation (e.g. teacher‑–student) for transferring state‑based policies to perception‑driven ones.
• Publications in top ML or robotics conferences (e.g. NeurIPS, ICML, CoRL, RSS, ICRA).

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

$187,000—$292,000 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.

Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.

Agility Robotics does not accept unsolicited referrals from third‑party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.