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NVIDIA

Designs the chips and software that power AI

Solutions Architect

Full-TimeUpdated on 10/15/2026
No salary listed
Mid
Master's, PhD
Taipei City, Taiwan
Remote
Solution EngineeringPre-Sales Solution Engineering

About the job

Requirements
  • A Master of Science or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Physics, Atmospheric Science, Applied Mathematics, or a related technical field, or equivalent experience.
  • At least three years of experience in AI, machine learning, scientific computing, high-performance computing, or solution architecture.
  • Strong programming skills in Python.
  • Familiarity with deep learning frameworks such as PyTorch.
  • Experience with Linux development environments and GPU computing.
  • Ability to engage technical and executive audiences through communication and presentations.
  • Ability to work independently and collaborate across global engineering, product, and sales teams.
Responsibilities
  • Drive customer adoption of NVIDIA Physical AI and AI for Science solutions across Taiwan.
  • Engage government agencies, research institutions, universities, and enterprise customers to architect and deploy AI solutions for scientific computing, weather forecasting, engineering simulation, and digital twins.
  • Lead technical engagements involving PhysicsNeMo, Weather AI, Earth-2, Omniverse, Isaac Sim, and related Physical AI technologies.
  • Design and optimize end-to-end AI workflows on NVIDIA accelerated computing platforms.
  • Collaborate with internal engineering and product teams to accelerate customer adoption of new NVIDIA technologies.
  • Develop reference architectures, technical assets, demonstrations, and best practices for use across Taiwan and APAC.
  • Deliver technical workshops, hands-on training, and executive briefings for customers and ecosystem partners.
  • Support strategic AI initiatives and ecosystem development in Taiwan.
Desired Qualifications
  • Proficiency in Physics-informed Neural Networks (PINNs), Neural Operators, or AI-based numerical simulation.
  • Knowledge of Weather AI, Earth-2, climate modeling, computational fluid dynamics, finite element analysis, or other scientific simulation workloads.
  • Experience with Omniverse, Isaac Sim, Cosmos, robotics simulation, or digital twin applications.
  • Experience with Slurm, Kubernetes, or distributed AI infrastructure.
  • Publications, open-source contributions, or technical leadership in AI for Science or Physical AI.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

Company Equity

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Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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