Robotics Integration Intern
Multiple Teams
Updated on 9/23/2025

Figure
No salary listed
San Jose, CA, USA
In Person
Figure is an AI Robotics company developing a general-purpose humanoid robot to address labor shortages and eliminate unsafe or undesirable work. We’re building intelligent, reliable machines to work alongside humans and revolutionize the future of labor. We are seeking a Robotics Integration Intern for Winter 2026 with a focus on controls, behaviors, and software integration. You’ll work directly with the system integration team to develop behaviors, write test scripts, and support the debugging and validation of full humanoid robot systems. This role is hands-on, highly technical, and ideal for someone passionate about full-stack robotics integration. This internship is designed for students in their final year of an undergraduate or master’s program, as well as recent graduates who are on track to complete their degree by the end of 2026, or the following year.
Responsibilities:
- Develop and execute robot behaviors for system-level testing, bring-up, and validation.
- Write software tools and scripts (C++, Python) to support integration, test automation, and data analysis.
- Assist in debugging complex hardware-software integration issues across mechanical, electrical, and control systems.
- Analyze system-level performance data to support root cause investigations and improve robot behavior.
- Collaborate with senior engineers on validation plans that exercise the full robot under real-world conditions.
Requirements:
- Currently pursuing a Bachelor’s, Master’s, or PhD in Robotics, Controls, Computer Science, Mechanical, Electrical, or related fields.
- Coursework or project experience in robotics controls, kinematics, or real-time systems.
- Strong programming skills in C++ and Python.
- Familiarity with robotic systems integration and hardware/software debugging.
- Comfortable working hands-on in a fast-paced hardware lab environment.
Bonus Qualifications:
- Experience with ROS2, behavior trees, or motion planning frameworks.
- Background in humanoid, legged, or high-DOF robotic systems.
- Familiarity with Linux, version control (Git), and real-time logging tools.

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