Senior Solution Architect - AI Development

NVIDIA; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

A leading tech firm in Singapore is seeking a highly skilled NIM Solution Architect. The role involves implementing NVIDIA's Inference Microservice solutions and optimizing AI workflows. Candidates should have over 7 years of experience in AI technologies, strong programming skills, and a proven track record with large language models. This position offers the opportunity to work in a cutting-edge environment focused on the future of AI.

Qualifications

• 7+ years of experience.
• Proven experience in deploying and optimizing large language models.
• Strong programming skills in Python or C++.

Responsibilities

• Drive the implementation of NVIDIA Inference Microservice solutions.
• Deploy optimized models into containers.
• Provide technical support and mentorship to customers.

Skills

Experience with large language models

Proficiency in Python or C++

Problem-solving skills

Collaboration skills

CUDA optimization experience

Education

Bachelor's in Computer Science or related field

Tools

TensorRT

Docker

Git

CI/CD practices

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

NVIDIA leads the computing future, guided by our dedication to innovation and quality. As a NIM Solution Architect, you will help build AI computing, applying NVIDIA's advanced technologies to optimize models, develop AI workflows, and support customers with advanced solutions.

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