About the RoleThe AI Controls team builds high-rate learned controllers that let Digit move robustly, efficiently, and safely in dynamic environments. As an AI Controls Engineer, youll 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 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.Apply Now: https://grnh.se/b444bbd04us
