AI Factory Digital Twin Engineer at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, HPCIndustries

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

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 contribute to industry standards (ASHRAE, ASME, OCP) for digital twin development

Skills

Key technologies and capabilities for this role

CFDFNMmulti-physics simulationANSYS-FluentSTAR-CCM+FlownexSolidWorksNXRevitNVIDIA OmniversePythonC++MATLABSCADABMS

Questions & Answers

Common questions about this position

What is the salary or compensation for this AI Factory Digital Twin Engineer role?

This information is not specified in the job description.

Is this position remote or does it require working from an office?

This information is not specified in the job description.

What key skills and experience are required for this role?

Candidates need a Master’s or Ph.D. in Mechanical Engineering or related field, 8+ years in CFD, flow network modeling, and system-level simulation, deep proficiency with Ansys Fluent, STAR-CCM+, Flownex or equivalent, advanced 3D CAD modeling skills, and strong Python and C++ programming for automation.

What does the team collaboration look like at NVIDIA for this position?

The role involves collaborating across teams and partners to align modeling with design and operations, and contributing to industry standards like ASHRAE, ASME, and OCP for digital twin development.

What makes a strong candidate for this Senior AI Factory Digital Twin Engineer position?

A strong candidate will have a Master’s or Ph.D., 8+ years of CFD and simulation experience in data centers, proficiency in tools like Ansys Fluent and STAR-CCM+, CAD modeling, Python/C++ automation, and experience with Omniverse and operational data integration.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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