Nvidia Solutions Architect LLM 

Taiwan, Taipei 

79035675

As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns.

What you’ll be doing:

• Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI.

• Help customers build their large-scale projects, especially Large Language Model (LLM) projects.

• Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines.

• Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

• Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures.

What we need to see:

• MS or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience).

• 3+ years of work-related experience in AI for natural language processing (NLP) and large language model (LLM).

• Knowledge of application areas such as natural language processing and computer vision.

• Excellent programming skills in some rapid prototyping environments such as Python, C++ and parallel programming (e.g., CUDA) is a plus.

• Expertise with deep learning frameworks such as PyTorch.

• Strong written and oral communications skills in English.

Ways to stand out from the crowd:

• Background in large language model.

• Demonstrated experience optimization workloads with GPU technology.

• Experience with NVIDIA AI and Data Science software and platform.