About the position
Agility Robotics 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. We're looking for an experienced engineer to lead the integration of learned skill policies into our production stack. In this role, you'll work closely with our Skills and AI teams on bridging upstream innovation and real-world deployment. You will be responsible for defining how learned skill policies mesh with other classical methods. You'll also contribute to defining our long-term technical roadmap for how learning fits into robot skill execution.
Responsibilities
- Lead the integration of AI-driven behaviors into our skill framework, ensuring they are robust, testable, and production-grade.
- Define best practices and infrastructure for evaluating, curating, and integrating learned skill policies.
- Drive the development of data collection workflows (e.g., teleop), including annotation, quality control, and feedback loops with our AI team.
- Develop and maintain high-quality interfaces between the learned skill policies and orchestration and execution layers (e.g., behavior trees, state machines, task planners).
- Build internal tools to support rapid iteration of the collect > train > evaluate > deploy loop.
- Contribute to on-robot testing and analysis to evaluate real-world performance and identify bottlenecks.
- Replay and analyze failed robot trajectories to identify root causes, and collect targeted teleop data to address specific failure modes and gaps in the training dataset.
- Set up training environments, run and evaluate training scripts, and analyze policy performance on real hardware.
- Help shape the long-term vision for RL policy integration in production skills.
Requirements
- You have a BS, MS, or PhD in Computer Science, Robotics, or a related field.
- You have 5+ years of professional experience working at the interface between robotics and learning-based control, whether that's policy integration, imitation learning, or deploying RL in the real world.
- You write modern Python code and have strong software fundamentals.
- You care about system performance and reliability, and know how to build evaluation pipelines.
- You are hands-on and passionate about seeing your work running on real robots, in the real world, in production, not just in sim or in isolation.
- You are pragmatic: you value simplicity and leverage proven technologies when they get the job done.
Nice-to-haves
- Prior experience with imitation learning, offline RL, or learned policy deployment on humanoid robots.
- Experience collecting and using teleop data in production ML pipelines.
- Experience working with robot sensors (e.g., F/T, RGBD) for manipulation or locomotion tasks.
Benefits
- 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 10 company holidays, including a winter shutdown. Non-Exempt Employees: 10 vacation days, paid sick leave, and 10 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.
