Senior Timing CAD Engineer, Applied AI
NVIDIA
PythonPyTorchRayTensorflow
AI Factory Digital Twin Engineer
NVIDIA
full-time
Posted on:
Location Type: Hybrid
Location: Santa Clara • California • 🇺🇸 United States
Visit company websiteSalary
💰 $152,000 - $247,250 per year
Job Level
SeniorLead
Tech Stack
Python
About the role
- 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.
Requirements
- Master’s or Ph.D. in Mechanical Engineering, Thermal/Computational Engineering, 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.
Benefits
- equity
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Applicant Tracking System Keywords
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Hard skills
CFDflow network modelingsystem-level simulation3D CAD modelingthermofluid dynamicsmulti-phase heat transferPythonC++MATLABAI-based parameter studies
Soft skills
collaborationleadershipcommunication
Certifications
Master’s in Mechanical EngineeringPh.D. in Mechanical EngineeringThermal/Computational Engineering
