Solutions Architect job opportunity at NVIDIA.

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DatePosted 17 Days Ago bot
NVIDIA Solutions Architect
Experience: 6-years
Pattern: full-time
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loacation Taiwan, Taipei, Taiwan
loacation Taiwan, Taipei....Taiwan

We are looking for a Solutions Architect to work with AI for Healthcare and Life Sciences 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: Design and implement end‑to‑end AI pipelines for medical imaging, sensor fusion, and real‑time inference using platforms such as MONAI, Holoscan, and Clara. Collaborate with hospitals, academia, med‑tech, and health‑IT partners to translate clinical workflows into deployable, regulatory‑compliant AI systems. Build reusable reference architectures and toolkits for imaging, robotics‑assisted surgery, and smart‑hospital applications. Optimize model performance and deployment on NVIDIA platforms including DGX, IGX, and edge systems powered by Holoscan. Lead proof‑of‑concept and production projects with healthcare customers, ensuring reliability, scalability, and data‑security compliance. Partner with internal teams to scale validated AI architectures and best practices across the healthcare ecosystem. What we need to see: Master’s degree or Ph.D. in Computer Science, Biomedical Engineering, or related field. 6+ years of experience in AI development, medical imaging, or edge‑computing applications. Proficient in Python and deep learning frameworks such as PyTorch, with hands-on experience using MONAI for medical imaging model training, inference, and optimization. Familiarity with DICOM, PACS/VNA systems, and clinical‑data integration workflows. Strong proficiency in Python and experience deploying AI on GPU‑accelerated platforms. Excellent communication and technical leadership skills. Ways to stand out from the crowd: Experience with MONAI, Holoscan, Clara, or related NVIDIA healthcare SDKs. Knowledge of medical‑device development cycles or TFDA/FDA regulatory frameworks. Background in real‑time or low‑latency vision and sensor‑processing pipelines. Proven track record delivering AI solutions in clinical or hospital environments.

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