Robot Learning Engineering Intern

Job Description

Robot Learning Engineering Intern | Agility Robotics

The Tone:
This is an internship at Agility Robotics, located in Pittsburgh, PA. Agility Robotics develops commercially deployed humanoids that operate alongside teams in warehouses, manufacturing facilities, and distribution centers. This role is crucial for supporting the development of learned manipulation behaviors, enabling robots to tackle physically demanding tasks and pioneering a new era of automation that enhances human potential.

The TL;DR
• Role: Internship
• Type: Temporary (3-6+ months)
• Location: In-person, Pittsburgh, PA
• Pay: $55 hourly
• Team: Skills team
• Mission: Support the development and validation of learning workflows for learned manipulation behaviors on humanoid systems.
• Tech Stack: Python

What You’ll Actually Do
• Data Collection: Support demonstration data collection for learned robot behaviors using teleoperation and other operator-in-the-loop systems.
• Testbed Development: Help build and improve a robot learning testbed, including integration of teleop interfaces, cameras, and other sensing required for data collection and evaluation.
• Experiment Support: Assist with experiments focused on contact-rich or force-aware manipulation behaviors.
• Tooling Improvement: Build and improve tooling for data ingestion, annotation, validation, replay, and analysis.
• Policy Evaluation: Assist in evaluating learned policies in simulation and on real robot hardware.

The Must-Haves
• Background: Currently pursuing an MS or PhD in Robotics, Computer Science, Machine Learning, or a related field.
• Experience: Strong software engineering fundamentals, a background in robotics, machine learning, embodied AI, controls, or autonomous systems, and familiarity with imitation learning, reinforcement learning, robot manipulation, force control, teleoperation, robot sensors, or object perception.
• Skills: Proficiency in Python, strong analytical, experimental, and debugging skills, and comfort working hands-on with robotic systems in a lab environment.
• Bonus: Experience with behavior cloning, Learning from Demonstration, offline RL, or learned control policies; experience with robot data collection systems, VR/XR tools, haptics, or teleoperation interfaces; experience with force/torque sensing or contact-rich manipulation tasks; or experience evaluating algorithms on real hardware rather than simulation alone.