Robotics Research Engineer

Foundry Robotics•San Francisco, CA

1d•Onsite

About The Position

We are reimagining manufacturing through advanced robotics. Our mission is to rebuild the American manufacturing industry as an AI-first, assembly-focused, dual-use contract manufacturer. We aim to empower manufacturers with intelligent, efficient, and adaptable robotic systems that redefine productivity and quality. As a founding member of our engineering team, you will have a direct and significant impact on our product, culture, and ultimate success. This role is 100% in-person at our office in the mission, SF. The Role We are hiring a Robotics Research Engineer to design, implement, and deploy intelligent robotic systems for manufacturing. This is not a purely academic role — and not a generic software role. You will work across: ROS2-based system architecture Manipulation and navigation Perception and VLA-based control Traditional controls fused with learned methods On-site deployment in production manufacturing workcells You should be equally comfortable reading robotics papers, tuning controllers, debugging sensor calibration, and pushing production code to robots running on a factory floor.

Requirements

Experience shipping systems into real environments (not just lab demos)
Comfort debugging hardware–software integration issues
Ability to own systems end-to-end
Thrives in high-velocity, ambiguous environments
Takes full technical ownership of complex systems
Willing to get into the weeds of mechanical, electrical, and software challenges

Nice To Haves

PhD in Robotics or related field
Experience working on dual-use or DoD-related systems
Ability to obtain a government security clearance
Experience with safety-critical robotic systems

Responsibilities

Design and implement distributed robotic systems in ROS2
Build modular autonomy stacks for manipulation and mobile platforms
Own system-level performance, latency, and reliability
Develop and integrate Vision–Language–Action models for robotic control
Design data collection pipelines and fine-tune foundation models for assembly tasks
Benchmark and evaluate real-world performance
Fuse traditional control with learned policies
Implement hybrid perception–planning–control architectures
Improve robustness, repeatability, and safety in physical systems
Develop algorithms for dexterous manipulation and industrial navigation
Ship systems from prototype to production
Debug real-world edge cases (lighting, calibration drift, wear, latency) and maintain deployed robotic cells