Are you a computational scientist, engineer or data scientist passionate about working on the frontiers of artificial intelligence and high performance computing (HPC)? NVIDIA is searching for a Solutions Architect to work with our customers in higher education and research. Solutions Architects are drawn from outstanding developers and scientists who enjoy helping our customers use the NVIDIA platform to make ground-breaking advances. We need people who can develop positive relationships with customers, learn their requirements and work to bring solutions that enable their success.
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 20% 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:
BS, 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 fundamentals in programming, problem-solving and debugging skills
Excellent presentation, communication and collaboration skills
Ways to stand out from the crowd:
Experience working with the academic research community supporting HPC or AI
Full-stack scientific computing experience including parallel programming in languages such as C/C++, Python, CUDA, OpenACC, OpenMP and MPI.
Experience designing and implementing computing infrastructure to support AI and HPC workloads.
Experience with orchestration and containerization tools used to manage a shared computing environment. (e.g. Slurm, Kubernetes, NVIDIA Base Command Manager, Docker, Apptainer/Singularity)
You will also be eligible for equity and benefits.