General-purpose humanoid robotics with custom silicon and learned control
Foundation is building hardware and software for general-purpose humanoid robots, founded in 2024 and now scaling fast across 51–200 employees. The stack reveals a hardware-first, in-house capability strategy: custom PCB design (Altium, KiCad), mixed-signal electronics (Cadence, ANSYS), FPGA/ASIC work (Verilog, SystemVerilog), real-time embedded (ARM, RTOS, VxWorks, FreeRTOS), and ML inference (PyTorch, JAX, TensorFlow, ORB-SLAM3). The hiring velocity—29 engineering roles out of 38 open, weighted toward senior and lead levels—tracks a concurrent factory ramp and a push to eliminate vendor reliance through custom inference silicon and PCB controllers.
Notable leadership hires: Motor Actuator Lead, Chief of Staff
Foundation develops general-purpose humanoid robots designed to operate in high-risk and labor-intensive environments. The company's charter is to address structural labor shortages in industries like conflict response and manufacturing by building robots capable of complex, real-world task execution. Engineering is the core of the operation: the team spans embedded systems, hardware design, ML/RL, sensor integration, and factory production. Current priorities include real-time locomotion and control, in-house RL training pipelines, custom inference chip evaluation, and manufacturing scale-up. The organization is headquartered in San Francisco and hiring exclusively in the United States.
Foundation uses embedded C, C++, ARM, RTOS (FreeRTOS, VxWorks), ROS 2, PyTorch, JAX, TensorFlow, ORB-SLAM3, FPGA/ASIC design (Verilog, SystemVerilog), and real-time control stacks. They are actively evaluating CUDA and custom inference chips.
Current projects include custom electronics and PCBs for robotic controllers, factory launch, sensor integration, custom inference chip evaluation, in-house RL training pipelines, real-time humanoid locomotion control, and hardware-in-the-loop validation on real robot platforms.
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Foundation'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.