Senior Solutions Architect, AI Cloud Services

Interested in being a part of a team that brings Artificial Intelligence (AI) to some of the biggest customers in the world? NVIDIA is looking for an experienced Solutions Architect to assist customers with adoption of GPU hardware and software as well as building Machine Learning (ML), Deep Learning (DL), Data Analytics and other related topics on various Cloud Computing Platforms.

As part of the NVIDIA Solutions Architecture team, you will be the first line of technical expertise between NVIDIA and our customers and will engage developers, researchers, and data scientists with some of NVIDIA's most strategic technology as well as work closely with business and engineering on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions incorporating NVIDIA's full stack of technologies for customers business needs.

What you’ll be doing:

• Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s groundbreaking software and hardware technologies.
• Build and deploy solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.
• Build custom PoCs for solutions that address customer's critical business needs while applying NVIDIA's hardware and software technologies.
• Partner with Sales Account Managers or Developer Relations Managers to identify and secure business opportunities for NVIDIA products and solutions.
• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions.
• Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

What we need to see:

BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields or equivalent experience.

4+ years of Solutions Engineering (or similar Sales Engineering roles) experience.

Established track record of deploying AI/ ML solutions in cloud environments including AWS, GCP, Azure or OCI

Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes, data center deployments, etc.

Effective time management and capable of balancing multiple tasks.

Ability to communicate ideas clearly through documents, presentation, etc.

Ways to stand out from the crowd:

AWS, GCP, Azure or OCI Professional Solution Architect Certifications

Hands-on experience with NVIDIA GPUs and SDKs (i.e. CUDA, Triton, TensorRT-LLM, etc.)

Deep understanding of the full software development lifecycle, including best practices for system design, architectural patterns, and comprehensive testing.