Nvidia AI Factory Digital Twin Engineer 

United States, Texas 

339336103

What You Will Be Doing:

• Design and develop digital twins for NVIDIA’s AI Factories, integrating thermofluidic, electrical, and mechanical domains into unified simulation frameworks.

• Build and lead CFD, FNM, and CAD-based SimReady models using ANSYS-Fluent, STAR-CCM+, Flownex, SolidWorks, NX, or Revit, and prepare USD datasets for NVIDIA Omniverse.

• Automate simulation and optimization workflows with Python, C++, or MATLAB, applying AI-based parameter and sensitivity studies.

• Integrate operational data from SCADA, BMS, power, and thermal systems into digital twins to simulate, predict, and optimize factory performance; develop AI models to improve tokens/W and system efficiency.

• Validate simulations with site data and define operational envelopes for safe and efficient cooling and energy system operation.

• Collaborate across teams and partners to align modeling with design and operations, and chip in to industry standards (ASHRAE, ASME, OCP) for digital twin development.

What we need to see:

• Master’s or Ph.D. in Mechanical Engineering,Thermal/ComputationalEngineering, or a related field (or equivalent experience).

• 8+ years of experience in CFD, flow network modeling, and system-level simulation for large-scale industrial or data center environments.

• Deep proficiency with Ansys Fluent, Cadence, Siemens STAR-CCM+ / Simcenter, Flownex, or equivalent.

• Advanced skills in 3D CAD modeling (NX, CATIA, SolidWorks, Revit) and creating simulation-ready geometries and metadata.

• Strong programming skills in Python and C++, with experience automating simulation workflows, building APIs, and developing Omniverse extensions.

• Experience with USD-based asset structures, Omniverse platform integration, and creation of SimReady digital twin content.

• Solid foundation in thermofluid dynamics, multi-phase heat transfer, and system-level coupling of mechanical, electrical, and control systems.

• Demonstrated experience incorporating live operational data into predictive simulation environments to drive AI-based real-time control.

• Proven ability to analyze simulation outcomes to maximize tokens/W, PUE, and overall AI Factory efficiency.

Ways to stand out from the crowd

• Background in AI/HPC data center cooling, including immersion and two-phase systems.

• Experience building predictive digital twin frameworks combining physical modeling with ML-based optimization.

• Familiarity with MEP system design and controls integration in data centers or other mission-critical facilities.

• Prior contributions to standards organizations such as ASHRAE, ASME, or OCP advancing digital twin interoperability.

• Experience applying AI/ML for simulation acceleration, surrogate modeling, or predictive maintenance.