Nvidia Senior Solution Architect - AI Development 

Singapore 

450506379

What You’ll Be Doing:

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

• Apply 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, aiding them in building high-performing NIMs

• Build 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 mentorship to customers, facilitating the adoption and implementation of NVIDIA technologies and products

• Collaborate with multi-functional teams to develop and broaden our AI solutions portfolio

• Be an internal advocate for NVIDIA software and total solutions within the technical community

• Position yourself as an inspiring leader in the industry by incorporating NVIDIA technology, especially inference services, into LHA, business partners, and the broader community and Assist in supporting the NVAIE team and driving NVAIE business in China

What We Need To See:

• 7+ years of experience.

• Bachelor's or equivalent experience in Computer Science, Artificial Intelligence, or a relevant 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 mainstream inference engines (e.g., vLLM, SGLang)

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

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

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

• Experience in architectural build for field LLM project. Expertise in model optimization techniques, particularly using TensorRT

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

• CUDA optimization experience and extensive experience in crafting and deploying large-scale HPC and enterprise computing systems