Relativity Space
Robotics Kinematics Engineer II
About this role
Relativity Space seeks a Robotics Kinematics Engineer II to develop and maintain kinematics algorithms and calibration software for advanced robotic systems used in additive manufacturing. You'll own the kinematics library infrastructure, serve as the technical expert for motion modeling, and work cross-functionally with welders, data scientists, and material scientists in a fast-paced R&D environment.
What you'll do
- Develop advanced kinematics algorithms for 6+ DoF robotic systems including forward/inverse kinematics and redundancy resolution optimized for real-time performance
- Own and maintain the kinematics library shared across multiple robotics software products
- Develop and maintain calibration tools and methodologies supporting diverse robot calibration workflows
- Serve as Subject Matter Expert for robot kinematics, motion modeling, and multi-axis synchronization
- Collaborate with cross-functional teams to integrate kinematics solutions into manufacturing systems
- Navigate ambiguity and ownership in full-project lifecycle from design to deployment
What they're looking for
- Robotics kinematics (forward/inverse kinematics, redundancy resolution)
- Real-time algorithm optimization and performance tuning
- Software development and library architecture
- Robot calibration methodologies
- Motion modeling and multi-axis control
- C++ or Python for robotics applications
- Control systems theory
- Cross-functional collaboration and technical communication
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Relativity Space
Relativity Space develops the Terran R reusable rocket and is hiring engineers to design, manufacture, and launch it. The company seeks Manufacturing Engineers, Launch Integration Engineers, Vehicle Structures Engineers, and Avionics Hardware Engineers to work on critical flight systems, production processes, and launch operations at Cape Canaveral.
- Website
- relativityspace.com
Likely interview questions
- Describe your experience developing forward and inverse kinematics algorithms; how have you optimized them for real-time performance?
- Tell us about a time you owned a full project from design through deployment in an R&D environment—how did you handle ambiguity?