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Solutions Architect

NVIDIA Corporation

Taiwan, TaipeiPosted Aug 21, 2026
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Skills named in this posting

  • Python
  • PyTorch / TensorFlow
We are looking for a Solutions Architect to work with AI for Sciences researchers in Taiwan, focused on academic society to adopt NVIDIA GPU platform on VLM, Digital Twin, AI, Accelerated Analytics, Simulation, Deep Learning or Machine learning technologies. NVIDIA’s platform for HPC/MIG and Omniverse (OM), deep learning and high-performance computing have already made a major impact on industry. At NVIDIA, our Solution Architects are drawn from elite developers and scientists who enjoy working with the latest GPU hardware and software. We need a passionate, hard-working, and creative individual to help us pursue more of these opportunities in fields. Your primary focus is on AI for Sciences with researchers and developers at universities, research institute and labs. What you'll be doing: • Drive customer adoption of NVIDIA Physical AI and AI for Science solutions across Taiwan. • Engage with 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, demos, and best practices that can be leveraged 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. What we need to see: • MS, or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Physics, Atmospheric Science, Applied Mathematics, or a related technical field (or equivalent experience). • 3+ years of experience in AI, machine learning, scientific computing, HPC, or solution architecture. • Strong programming skills in Python. • Familiarity with deep learning frameworks such as PyTorch. • Experience with Linux development environments and GPU computing. • Excellent communication and presentation skills with the ability to engage both technical and executive audiences. • Ability to work independently while collaborating effectively across global engineering, product, and sales teams. Ways to stand out from the crowd: • Proficiency in Physics-informed Neural Networks (PINNs), Neural Operators, or AI-based numerical simulation. • Knowledge of Weather AI, Earth-2, climate modeling, CFD, FEA, 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. With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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