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Freeform Tech Stack

AI-native metal 3D printing systems for industrial-scale manufacturing

Industrial Automation Hawthorne , CA 51–200 employees Founded 2019 Privately Held

Freeform builds integrated hardware-software systems for metal additive manufacturing, with a tech stack anchored in low-level systems (C++, Rust, FPGA, GPU, CUDA) and mechanical design tools (NX, SolidWorks, Zemax). The engineering-heavy hiring profile—30 of 43 active roles—paired with active projects spanning custom electronics, HPC-based real-time simulation, and petabyte-scale telemetry reflects a company scaling from prototype toward production systems. Pain points cluster around physics-based modeling, GPU simulation performance, and post-processing automation, signaling the operational complexity of turning algorithmic gains into factory throughput.

Tech Stack 50 technologies

Core StackC++ Go Rust Python MATLAB Rippling Flask Django React Next.js NetSuite SAP Figma QuickBooks Oracle SolidWorks RTOS FPGA GPU NX C/C++ JMP Minitab CUDA HPC NVLink InfiniBand Fishbowl Zemax FPGAs+19 more

What Freeform Is Building

Challenges

  • Continuous improvement in r&d
  • Designing custom electronics for metal 3d printing
  • Scaling metal 3d printing production
  • Physics-based modeling for metal 3d printing
  • Real-time simulation on gpu
  • Streamlining post processing operations
  • Post-processing of metal 3d printed parts
  • Improving factory system reliability
  • Enhancing performance of autonomous metal 3d printing
  • Improving yield and throughput

Active Projects

  • Custom electronics for metal 3d printing factory systems
  • Real-time simulation on hpc or gpu platforms
  • High-speed data acquisition system
  • First production scale metal 3d printing factory capability
  • Custom precision mechanical systems for metal 3d printing
  • Scaling in-house mechanical build processes
  • Precision alignment process
  • Production-scale metal 3d printing system
  • System level integration and validation
  • Petabyte-scale telemetry storage and retrieval systems

Hiring Activity

Accelerating45 roles · 40 in 30d

Department

Engineering
30
Manufacturing
6
Finance
2
HR
2
Design
1
Ops
1
Supplychain
1

Seniority

Senior
19
Mid
12
Junior
4
Principal
4
Manager
2
Intern
1
Lead
1

Notable leadership hires: Technical Lead

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About Freeform

Freeform designs and operates metal 3D printing factories powered by AI and custom hardware. Founded in 2019 and headquartered in Hawthorne, California, the company unifies software control, bespoke electronics, mechanical systems, and physics simulation into a single manufacturing platform. Their current focus spans production-scale system integration, real-time simulation on GPU/HPC clusters, high-speed sensor data acquisition, and yield optimization. The product targets industrial customers seeking to produce complex metal parts at volume without traditional tooling constraints.

HeadquartersHawthorne , CA
Company Size51–200 employees
Founded2019
Hiring MarketsUnited States

Frequently Asked Questions

What technology does Freeform use to build 3D printing systems?

Freeform's stack includes C++, Rust, FPGA, GPU (CUDA), and HPC for real-time simulation; NX and SolidWorks for mechanical design; and Zemax for optical systems. They pair low-level systems programming with physics modeling and custom electronics for metal 3D printing hardware.

What is Freeform working on?

Freeform is building production-scale metal 3D printing factories with focus on custom electronics design, real-time GPU-based simulation, petabyte-scale telemetry systems, precision mechanical alignment, and post-processing automation to improve yield and throughput.

How this profile is built

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.