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.
Solid working knowledge of Python
System-level experience, specifically GPU-based systems
We make extensive use of conferencing tools, but occasional travel is required for local on-site visits to customers and industry events. We are open to remote work locations!
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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Skills Required
- Bachelor’s, master’s, or doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, another engineering field, or equivalent experience
- 4 or more years of Solutions Engineering or similar Sales Engineering experience
- Demonstrated experience deploying AI or machine learning solutions in cloud environments, including AWS, GCP, Azure, or OCI
- Knowledge of DevOps or MLOps technologies, including Docker, containers, Kubernetes, and data center deployments
- Effective time management and ability to balance multiple tasks
- Ability to communicate ideas clearly through documents and presentations
- AWS, GCP, Azure, or OCI Professional Solution Architect certification
- Hands-on experience with NVIDIA GPUs and SDKs such as CUDA, Triton, or TensorRT-LLM
- Understanding of the full software development lifecycle, system design, architectural patterns, and comprehensive testing
- Solid working knowledge of Python
- System-level experience with GPU-based systems
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
