Solutions Architect AI and ML

About the Role

NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML) , Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms. As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science.

As a Solutions Architect AI and ML, you will be the first line of technical expertise between NVIDIA and our customers, engaging directly with developers, researchers, and data scientists. You will work with NVIDIA’s most strategic technology customers and collaborate directly with business and engineering teams on product strategy. This role focuses on driving end-to-end technology solutions, applying NVIDIA’s full set of technologies based on customer business needs.

What You Will Be Doing

• Collaborating with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologies.
• Building and deploying AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.
• Creating custom Proofs of Concept (PoCs) for solutions that address critical customer business needs by applying NVIDIA hardware and software technology.
• Partnering with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions in ML/DL and other software areas.
• Preparing and delivering technical content to customers, including presentations on purpose-built solutions and workshops on NVIDIA products.
• Conducting regular technical customer meetings for project/product roadmap, feature discussions, and introductions to new technologies.
• Establishing close technical ties to customers to facilitate rapid resolution of technical issues.

What We Need To See

• 3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience.
• 3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks like TensorFlow or PyTorch. GPU and CUDA experience is highly beneficial.
• BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.
• Established track record of deploying solutions in cloud computing environments including AWS, GCP, or Azure.
• Knowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, and data center deployments.
• Ability to use at least one scripting language (e.g., Python).
• Good programming and debugging skills.
• Ability to communicate ideas and code clearly through documents and presentations.

Ways To Stand Out From The Crowd

• AWS, GCP, or Azure Professional Solution Architect Certification.
• Hands-on experience with NVIDIA GPUs and SDKs (e.g., CUDA, RAPIDS, Triton).
• System-level experience, specifically with GPU-based systems.
• Experience with Deep Learning at scale.
• Familiarity with parallel programming and distributed computing platforms.

Key skills/competency

• Machine Learning (ML)
• Deep Learning (DL)
• GPU Hardware
• Cloud Computing
• TensorFlow/PyTorch
• CUDA
• AWS/GCP/Azure
• DevOps/ML Ops
• Python Programming
• Solution Architecture