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 use NVIDIA technology that will be adopted across all segments of the Energy industry including Oil and Gas, Renewables, and Power Utilities. At NVIDIA, our Solutions Architects are drawn from best-in-class developers and scientists who enjoy working with the latest in GPU and Networking hardware and software! NVIDIA’s platforms for artificial intelligence, neural networks, and high-performance computing have impacted the energy domain significantly. These platforms are widely used by leading energy companies and start-ups. Our success has been based on vertical 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 passionate, 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 clients and collaborators. They believe deep learning, data science, and artificial intelligence are a new computing revolution. These technologies have the potential to transform the energy domain.
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 mentor 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.
We make heavy use of conferencing tools, but some travel is required for this role. Be empowered to find the best way to get your job done and do what it takes to make our partners and customers successful.
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 efficiently collaborate with management and engineering.
Experience within the energy industry or with customers/partners in the energy domain.
Deep Neural Network and Machine Learning research and development experience with energy data.
Published record of thought leadership in a technical area or industry segment.
Strong analytical, time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into sophisticated projects.
Ways to stand out from the crowd:
Experience using data science in the energy industry.
Creative generation of synthetic data.
Experience using GPGPU programming and design practices.
CUDA programming and optimization experience.
Experience with network software development
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 individuals in the world working for us. If you're creative and autonomous, we want to hear from you!
#NALASAHiring
Skills Required
- MS or PhD in Engineering, Mathematics, Physics, Computer Science, or equivalent experience
- 8+ years of work-related experience in data science or software development
- Knowledge of parallel computing with GPUs
- Experience with Docker or container-based application deployment
- Experience with Kubernetes
- Experience with modern deep learning software architectures and frameworks
- Strong written and oral communication skills
- Experience collaborating with management and engineering teams
- Experience in the energy industry or with energy-domain customers or partners
- Deep neural network and machine learning research and development experience using energy data
- Published record of technical or industry thought leadership
- Strong analytical, time-management, organizational, and coordination skills
- Experience applying data science in the energy industry
- Experience generating synthetic data
- Experience with GPGPU programming and design practices
- CUDA programming and optimization experience
- Network software development experience
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.”
