AI Factory Digital Twin Engineer

NVIDIA•Us, CA

About The Position

NVIDIA’s AI Factories are built to accelerate AI and HPC workloads. At their core the Digital Twin (physics-based model used to design, validate, and operate factories optimized for tokens per watt across GPUs, cooling, power, and control systems. We are seeking a Senior AI Factory Digital Twin Engineer with expertise in CFD, FNM, multi-physics simulation, and digital twin integration to lead the development and operation of NVIDIA’s AI Factory digital twins, modeling MEP systems, integrating real-time data, and enabling predictive AI-based control of the infrastructure. You’ll be shaping the digital and physical foundation of NVIDIA’s AI Factories, engineering virtual replicas that not only design the future but also operate it in real time. Your models will guide NVIDIA in achieving the highest tokens per watt efficiency across global AI Factory deployments, uniting simulation, data, and AI to create the most advanced compute infrastructure on Earth.

Requirements

Master’s or Ph.D. in Mechanical Engineering, Thermal/Computational Engineering, or a related field (or equivalent experience).
12+ 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.

Nice To Haves

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.

Responsibilities

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.