AI-driven metal 3D printing systems for industrial-scale part production
Freeform builds production-scale metal additive manufacturing systems where printer hardware, control software and simulation are engineered as one stack. The tooling spans embedded C++/Rust on RTOS and FPGAs, CUDA with InfiniBand/NVLink HPC for real-time simulation, and optics design in Zemax, pointing to deep in-house hardware control. Hiring is overwhelmingly engineering-led, though velocity is slowing, while job posts flag parts-flow bottlenecks and R&D-to-production handoff as pressures.
Notable leadership hires: Technical Lead
Freeform is a Hawthorne, California-based manufacturer developing AI-native metal 3D printing systems that produce industrial parts. Founded in 2019 and privately held, the company has 51–200 employees. Its work covers printer hardware, custom electronics, data acquisition, geometry processing and physics simulation, with a print factory that turns designs into finished metal parts. Business operations run on NetSuite and Oracle, with IT managed through Azure Entra ID, Intune and Ansible. Hiring is concentrated in the United States.
Freeform's stack includes C++, Rust, Go and Python, RTOS and FPGA embedded systems, CUDA with HPC, NVLink and InfiniBand, Zemax and NX for design, React and Next.js, Kubernetes, AWS and NetSuite.
Freeform is headquartered in Hawthorne, California, and hires in the United States. The privately held company was founded in 2019 and has 51–200 employees.
Freeform is building production-scale metal 3D printing systems and print factory capabilities, plus high-speed data acquisition, real-time simulation on HPC/GPU platforms, and a geometry processing pipeline.
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Freeform's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.