Nvidia Solutions Architect Manager 

United States, Texas 

96077895

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 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 advanced 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:

• Degree in Engineering, Mathematics, Physics, Computer Science or equivalent experience.

• 8+ overall years of work-related experience in data science or software development with knowledge of parallel computing with GPUs.

• 3+ years of management experience

• 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 supporting customers/partners in technical engagements.

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

• Strong analytical and problem-solving skills.

Ways to stand out from the crowd:

• Experience in team leadership and management.

• Experience applying data science to industry problems as well as experience using GPGPU programming and design practices.

• CUDA programming and optimization experience.

• Background with network software development.

• Experience with AI: Published record of thought leadership in a technical area or industry segment; Deep Neural Network research and development experience with industry data; Machine Learning research and development experience with industry data, etc.