Solutions Architect

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.

Your primary focus is on AI for Sciences with researchers and developers at universities, research institutes and labs.

Responsibilities:

• 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.

Requirements:

• 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.

Preferred Qualifications:

• 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.