mid software engineering Solutions Architect ic 2+ yrs Master's · Posted Apr 20, 2026

About this role

Nvidia is hiring a mid-level Solutions Architect in the software engineering function based in Taipei, Taiwan. The posting calls out experience with Python, CUDA, TensorFlow, PyTorch and roughly 2+ years of relevant work. Listed education preference: a master's degree or equivalent.

Role
Solutions Architect
Function
software engineering
Level
mid
Track
Individual contributor
Employment
Full-time
Location
Taipei, Taiwan
Experience
2+ years
Education
Master's degree
Posted
Apr 20, 2026
AI Summary
Solutions Architect designing and deploying GenAI models for AI for Sciences researchers in Taiwan. Requires Master's/Ph.D. in CS/Engineering, 2+ years ML/DL experience with hands-on work in speech, NLP, computer vision, or multimodal models. Must proficiently code in Python with PyTorch/TensorFlow and optimize models on NVIDIA GPUs.

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Job description

from Nvidia careers

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:

  • 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.

    This is an excerpt. Read the full job description on Nvidia careers →
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