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.
Your primary focus is on AI for Sciences with researchers and developers at universities, research institute and labs.
Key Responsibilities:
- 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.
- 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.
Requirements:
- Master's degree or Ph.D. in Computer Science, Biomedical Engineering, or related field.
- 3+ 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.
Nice to Have:
- 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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