Nvidia Senior Solutions Architect Higher Education Research 

United States, Texas 

677989865

Your primary responsibilities will be to lead HPC and AI technical engagements at universities and research institutions. You should be comfortable working in a dynamic environment, and have experience with HPC, deep learning and GPU technologies. Your ability to work independently is important, and you will rely upon your excellent interpersonal skills during customer engagements. We expect you to work collaboratively across the entire team, including sales, program management and business development.

What you’ll be doing:

• Engage customers with curiosity to understand their goals, strategies, and technical needs and help to deliver innovative solutions based on NVIDIA's accelerated computing platforms for ML/DL, data science and HPC.

• Stay abreast of the state of the art in scientific and AI computing ecosystems.

• Document what you know and teach others. This can include building targeted training, writing whitepapers, blogs, and wiki articles, and working through hard problems with a customer on a whiteboard.

• Provide customer requirements to engineering to foster product and platform improvements.

• We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and do what it takes to make our customers successful.

What we need to see:

• MS or PhD in Engineering, Mathematics, Physical Sciences, or Computer Science or equivalent experience.

• 5+ years relevant work experience.

• Experience porting and/or optimization scientific applications targeting GPUs.

• Excellent communication skills particularly in the presentation of highly technical material.

• Enjoy life-long learning, interacting with forward-thinking people, and staying at the forefront of the technology ecosystem.

• Strong analytical and problem-solving skills.

• Self-motivated and independent with the ability to multi-task effectively with minimal day-to-day direction.

Ways to stand out from the crowd:

• Full-stack scientific computing experience including parallel programming in languages such as C/C++, Python, CUDA, OpenACC, OpenMP and MPI.

• Background in working with technical computing customers.

• Experience designing and implementing computing infrastructure to support AI and HPC workloads.

• Experience with orchestration tools used to manage a shared computing environment. (e.g. Slurm, Kubernetes, NVIDIA Base Command Manager)