Nvidia Senior Solutions Architect Energy 

United States, Texas 

296437505

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.

• Detail what you know and teach 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 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 effectively collaborate with management and engineering.

• Experience in the energy industry or with customers/partners in the energy domain.

• Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into sophisticated projects.

• Strong analytical and problem-solving skills.

Ways to stand out from the crowd:

• Published record of thought leadership in Energy using HPC, Data Science, AI technology

• Creative generation of synthetic data.

• Experience using GPGPU programming and design practices.

• CUDA programming and optimization experience.

• Experience with AI: research and development in areas like ML, DL, design patterns like RAG.