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. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!What you will be doing:Working with Cloud Service Providers to develop and demonstrate solutions based on NVIDIA’s ML/DL and data science software and hardware technologiesBuild and deploy AI/ML solutions at scale using NVIDIA's AI software on cloud-based GPU platforms.Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technologyPartner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutionsPrepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issuesWhat we need to see:3+ years of Solutions Engineering (or similar Sales Engineering roles) or equivalent experience3+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.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 AzureKnowledge of DevOps/ML Ops technologies such as Docker/containers, Kubernetes, data center deploymentsAbility to use at least one scripting language (i.e., Python)Good programming and debugging skillsAbility to communicate your ideas/code clearly through documents, presentation etc.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 etc.)System-level experience specifically GPU-based systemsExperience with Deep Learning at scaleFamiliarity with parallel programming and distributed computing platformsWe make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 120,000 USD - 189,750 USD for Level 2, and 148,000 USD - 235,750 USD for Level 3.You will also be eligible for equity and benefits.Applications for this job will be accepted at least until September 26, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.