We are looking for a Solutions Architect to engage with customers, partners, and other NVIDIA software engineers to develop Energy specific applications and platforms that demonstrate NVIDIA technology that will be adopted across all segments of the Energy sector including Oil and Gas, Renewables, and Power Utilities. At NVIDIA, our Solutions Architects are drawn from elite developers and scientists who enjoy working with the latest in GPU and Networking hardware and software! NVIDIA’s platforms for machine learning, deep learning and high-performance computing have already made a major impact on the energy sector and are broadly used across leading energy companies and start-ups. Our success has been based on vertical focus industry business development, building a strong developer ecosystem, and scaling out the business using a broad partner channel including HW OEMs, Cloud Service Providers, Global System Integrators, and VARs.
We need a hardworking, and creative individual to help us pursue more of these opportunities in HPC, NLP, Machine Learning, Deep Learning, and Generative AI! This role requires becoming a trusted technical advisor and leader to our partners and customers who believe that deep learning, data science, and artificial intelligence is a new computing revolution and has the potential to transform the energy domain. A Solutions Architect is the bridge of technical expertise between our industry teams, our partners and customers. Dynamically engaging with internal developers, scientific researchers, data scientists, IT managers and senior leaders is an important part of the Solutions Architect role, and will give you experience with a range of partners and concerns.
What you will be doing:
Partner with our industry and account teams to develop a keen understanding of customer goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs.
Document what you know and guide others. This can vary from building targeted samples, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a customer on a whiteboard.
Be an industry leader with vision on integrating NVIDIA technology into AI, HPC, and enterprise GPU and networking architectures for sophisticated applications both in the datacenter and at the edge.
Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform.
What we need to see:
MS or PhD in Engineering, Mathematics, Physics, Computer Science or equivalent experience.
8+ years of work-related experience in data science or software development with knowledge of parallel computing with GPUs.
Background working with modern application deployment practices including but not limited to Docker/Containers and Kubernetes.
Experience with modern Deep Learning software architecture and frameworks.
Strong written and oral communication skills with the ability to optimally collaborate with management and engineering.
Background in the energy industry or engaging with clients/partners involved in the energy field.
Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects.
Ways to stand out from the crowd:
CUDA programming and optimization experience.
Experience using data science in the energy industry.
Experience using GPGPU programming and design practices.
Background with network software development
AI Exposure: Deep Neural Network or Machine Learning R&D with energy data.
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
- MS or PhD in Engineering, Mathematics, Physics, Computer Science or equivalent experience.
- 8+ years experience in data science or software development with knowledge of parallel computing with GPUs.
- Experience with Docker/Containers.
- Experience with Kubernetes.
- Experience with modern Deep Learning software architecture and frameworks.
- Strong written and oral communication skills.
- Background in the energy industry or experience engaging energy clients/partners.
- Strong time-management and organization skills coordinating multiple initiatives.
- CUDA programming and optimization experience.
- GPGPU programming and design practices experience.
- Experience using data science in the energy industry.
- Background with network software development.
- AI R&D experience (Deep Neural Network or Machine Learning with energy data).
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.”
