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.

• Design and develop reusable GenAI models and systems to support applied AI and AI for Science workflows.

• Build, maintain, and optimize scalable training and inference pipelines that can be reused across multiple projects and research collaborations.

• Collaborate with internal and external research partners to translate real-world requirements into robust, production-ready AI solutions.

• Deploy, profile, and optimize AI models on NVIDIA GPU platforms, ensuring reliability, performance, and efficient resource usage.

• Integrate AI components into end-to-end workflows, including world model and multi-agent–based applications, and ensure smooth interaction with existing systems.

• Master’s degree or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related field.

• 2+ years of experience in machine learning or deep learning, with hands-on work in at least one of the following areas: speech recognition, NLP/LLM, computer vision, or multimodal models.

• Proficiency in Python and experience with deep learning frameworks such as PyTorch or TensorFlow for training and deploying models.

• Strong understanding of model development workflows, including data preprocessing, experiment design, evaluation, and performance optimization.

• Experience working with cross-functional or research teams on prototypes, proof-of-concept systems, or applied research projects.

• Strong communication skills and the ability to work independently and collaboratively in a fast-paced environment.

• Experience with agent-based systems in real applications, such as interactive agents, workflow assistants, or knowledge-intensive tools.

• Familiarity with AI for Science or scientific computing workflows, such as simulation data analysis, experiment automation, or large-scale data processing.

• Experience deploying or optimizing models on NVIDIA GPUs, using CUDA, TensorRT, or other GPU-accelerated libraries and tools.

• Proven problem-solving skills, ownership mindset, and a focus on building scalable and reusable components.

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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