GrayMatter Robotics

HQ
Carson
90 Total Employees
Year Founded: 2020

GrayMatter Robotics Offices

GrayMatter Robotics is headquartered in Carson.

OnSite Workplace

Employees work from physical offices.

Our team works fully onsite at our headquarters in sunny Los Angeles, CA. We partner directly with each teammate to maintain flexibility and support the occasional work from home day.

Typical time on-site: 5 days a week

U.S. Office Locations

HQ
Carson

GrayArea

2226 E 223rd St, Carson, CA, United States, 90810

4 Days AgoSaved
In-Office
Los Angeles, CA, USA
Artificial Intelligence • Hardware • Productivity • Robotics • Software • Automation • Manufacturing
Paid robotics engineering internship supporting robotic grinding and surface-treatment applications. Responsibilities include designing, implementing, and testing robotic systems; partnering with application engineers; conducting system testing; supporting customer proof-of-concepts; and solving hands-on manufacturing challenges. The role is onsite in Carson, California, supports government projects, and runs approximately October 2026 through March 2027.
14 Days AgoSaved
In-Office
Los Angeles, CA, USA
Artificial Intelligence • Hardware • Productivity • Robotics • Software • Automation • Manufacturing
Manage government proposals, contracts, grants, compliance, financial reporting, budgeting, fund tracking, and audit documentation. Ensure adherence to FAR, DFARS, DCAA, SBIR/STTR, and grant requirements while supporting contract negotiations, modifications, renewals, and cross-functional execution with legal, finance, and operations teams.
19 Days AgoSaved
In-Office
Los Angeles, CA, USA
Artificial Intelligence • Hardware • Productivity • Robotics • Software • Automation • Manufacturing
Conduct foundation-model research for robotic manipulation and high-precision manufacturing. Responsibilities include data curation, simulation, model training, evaluation, rigorous testing on industrial robots, and deployment to production hardware. The intern will work independently on ambiguous AI problems, develop multimodal models, use reinforcement or imitation learning, collaborate cross-functionally, and write maintainable production-quality R&D code.