Nim Solution Architect jobs at Nvidia in China, Guangzhou City

What you’ll be doing:

• Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions

• Use NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers providing standardized API access for on-prem or cloud deployment

• Refine NIM tools for the community, help the community to build their performant NIMs

• Design and implement agentic AI tailored to customer business scenarios using NIMs

• Deliver technical projects, demos and client support tasks as directed by the Solution Architecture Leadership

• Provide technical support and guidance to customers, facilitating the adoption and implementation of NVIDIA technologies and products

• Collaborate with cross-functional teams to enhance and expand our AI solutions portfolio

• Be an internal champion for NVIDIA software and total solutions in technical community

• Be an industry thought leader on integrating NVIDIA technology especially inference services into LHA, business partners and whole community

• Assist in supporting NVAIE team and driving NVAIE business in China

What we need to see:

• 3+ years working experience with Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field

• Proven experience in deploying and optimizing large language models

• Proficiency in at least one inference framework (e.g., TensorRT, ONNX Runtime, PyTorch)

• Strong programming skills in Python or C++

• Familiarity with main stream inference engines (e.g., vLLM, SGLang)

• Experience with DevOps/MLOps such as Docker, Git, and CI/CD practices

• Excellent problem-solving skills and ability to troubleshoot complex technical issues

• Demonstrated ability to collaborate effectively across diverse, global teams, adapting communication styles while maintaining clear, constructive professional interactions

Ways to stand out from the crowd:

• Experience in architectural design for field LLM projects

• Expertise in model optimization techniques, particularly using TensorRT

• Knowledge of AI workflow design and implementation, experience on cluster resource management tools. Familiarity with agile development methodologies

• CUDA optimization experience, extensive experience designing and deploying large scale HPC and enterprise computing systems