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Foundational Industries

AI-native automation platform for autonomous factories

Emulation & Digital Twin Engineer

Software EngineeringConfirmed live in the last 24 hours
Full-timeCalifornia, USANo salary listed

About the Job

Requirements

  • Deep understanding of G-code and M-code dialects.
  • Experience with NC kernels, PLC logic, and servo behaviors.
  • Knowledge of machine coordinate systems, kinematics, and tool tables.
  • Experience with Fanuc CNC, FOCAS API, or ROBOGUIDE; Siemens SINUMERIK or Run MyVirtual Machine; Heidenhain iTNC; Haas NextGen Control; MTConnect; or OPC UA.
  • Experience building GPU-accelerated simulation workflows and importing CAD or robotics assets via SimReady OpenUSD templates.
  • Experience leveraging world models and reinforcement learning frameworks.
  • Mastery of OpenUSD composition, including layers, variants, and references.
  • Experience converting native CAM/CAD data to lightweight simulation schemas.
  • Knowledge of rigid-body dynamics and physics collision boundaries.
  • Experience writing ultra-low-latency, multithreaded code; deterministically mapping physical IoT data streams to 3D assets; containerization; and edge deployments.
  • Industrial interest in or experience with manufacturing, robotics, or industrial automation.

Responsibilities

  • Develop and integrate software-in-the-loop emulators for multi-axis CNC machines that mimic controller behaviors, acceleration and deceleration profiles, and real-time G-code and M-code execution.
  • Aggregate native machine CAD data and toolpath kinematics into OpenUSD format to create high-fidelity 3D machine environments in NVIDIA Omniverse.
  • Use NVIDIA Isaac Sim and Isaac Lab with physics engines such as PhysX to simulate robotic machine tending, chip clearance, and bin picking, including through integrated tools such as Fanuc ROBOGUIDE.
  • Implement NVIDIA Nemotron large and small language models to build agentic assistants that diagnose CNC alarm codes, translate conversational requests into machine macros, and generate Python code or G-code edits based on live simulation metrics.
  • Apply NVIDIA GR00T foundation models to train collaborative robots or dual-arm machine tenders to interact dynamically with varying components without rigid physical fixturing.
  • Establish low-latency data pipelines using OPC UA, MTConnect, or Siemens Industrial Edge to stream physical controller states to the Omniverse twin for real-time playback and predictive maintenance modeling.

About the Company

Foundational Industries

AI-native automation platform for autonomous factories

Foundational Industries builds an AI-native automation platform for industrial manufacturing that runs autonomous factories. The system uses edge computing, sensor fusion, Robotic Foundation Models, and multi-agent robotic arms under a single operating layer to design, manufacture, and ship products, with robots learning and improving in real time on the factory floor. It partners with AI-robotics suppliers and manufacturers to provide procurement and deployment of next-generation automation, aiming to increase automation density and reconfigure plants as needed. Its goal is to make reindustrialization practical by enabling domestic production of high-quality goods at competitive costs.

Company size
11-50
Company stage
Seed
Total funding
$25M
Headquarters
Mill Valley, CA
Founded
2026

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