We are now looking for a Solution Architect to join the America’s Partner Organization focused on HPC, Accelerated Analytics, Deep Learning and Machine Learning solutions with some GPU virtualization too.
If these areas are exciting to you, we should talk. NVIDIA is the world leader in GPU accelerated computing, and is looking for Solution Architects to engage our partners.
As a Solution Architect, you will work closely with partners in our North American region - establishing relationships, solving problems with their engineering teams, and helping them build a successful NVIDIA practice.
What you’ll be doing :
A huge part of the day-to-day job is staying up on the latest improvements in the ecosystem around GPU accelerated environments.
You'll also be called on to help architect and scale high-performance computing and virtual workstation environments that incorporate state of the art GPU technology.
Document what you know, and teach others. This can vary from building targeted training for partners and other Solutions Architects, to writing whitepapers, blogs, and wiki articles, to simply working through hard problems with a partner on a whiteboard.
Answer questions and provide mentorship. Work with Partner Business Managers to assist partners and customers on their mission critical projects.
You will help them to build their GPU enabled Accelerated Compute datacenters, and get the most out of their investment.
We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to figure out the best way to get your job done, and do what it takes to make our partners successful.
Above all, you will be the person that partners call on when they need to get technical in crafting solutions for customers that make use of NVIDIA technology.
Backed up by the other Solution Architects, the Engineering organization, and the whole of NVIDIA, you’ll get to be the face and brains of NVIDIA that our partners will learn to rely on.
What we need to see :
BS or MS in Engineering, Mathematics, Physics, or Computer Science.
8+ years of work related experience in software development or Machine learning or high-performance computing, GPU and CUDA experience highly desirable.
Experience working with DevOps including but not limited to Docker / Containers, Kubernetes and Data Center deployments.
Deep understanding of Dense Datacenter design including compute, Storage and networking.
Some experience with modern Deep Learning software architecture and frameworks.
Experience with supercomputing and technical computing environments
Ability to multitask effectively in a dynamic environment.
Strong analytical and problem-solving skills.
Clear written and oral communications skills with the ability to effectively collaborate with management and engineering.
Ways to stand out from the crowd :
Experience with Deep Learning frameworks, data-heavy applications, C and Python programming, shell scripting, virtualization, cloud services, and Linux
Have a willingness and ability to dig into unfamiliar territories to solve complex problems.