Are you a computational scientist or engineer passionate about working on the frontiers of artificial intelligence and high performance computing?
NVIDIA is searching for a Solutions Architect to work with our customers in Higher Education & Research and national labs. Solutions Architects are the primary technical contacts for our customers and engage deeply with scientific researchers and application developers. We need individuals 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 high performance computing (HPC) and deep learning technical customer engagements with a focus on developers and computational scientists at universities and research institutions. You should be comfortable working in a dynamic environment, and have experience with HPC, deep learning and software and systems. Your ability to work independently is important, and you will rely upon your excellent communication skills during consulting engagements. We expect you to work closely with the entire customer team, including sales, program management and business development. Some travel to conferences and customers will be required.
What you'll be doing:
* Engage with customers to develop a keen understanding of their goals, strategies, and technical needs - and help to define and deliver high-value solutions that meet these needs.
* Assist field business development in guiding the customer through the sales process for GPU Computing products, being responsible for the technical relationship and assisting customers in building creative solutions based on NVIDIA technology.
* Provide customer requirements to engineering to foster product and platform improvements.
* Be an industry leader with vision on integrating NVIDIA technology into HPC architectures.
* Be an internal champion for Deep Learning and HPC among the NVIDIA technical community.
What we need to see:
* MS or PhD in Engineering, Mathematics, Physical Sciences, or Computer Science.
* 4+ years of work related experience in software development or Machine Learning or HPC.
* Programming experience with HPC languages such as C/C++/Fortran, and data science languages like Python.
* Parallel programming experience with OpenMP/MPI.
* Experience with GPU Computing and CUDA/OpenACC programming.
* Experience working with supercomputing and technical computing customers.
* Experience with modern Deep Learning software architectures and frameworks including Tensorflow, PyTorch or other Deep Learning Frameworks
* Strong analytical and problem-solving skills.
* Self-motivated and independent with the ability to multi-task effectively with minimal day-to-day direction.
* Strong written and oral communications skills leading to effective collaboration with management and engineering.
Ways to stand out from the crowd:
* CUDA optimization experience.
* Computational Chemistry background.
* Experience programming embedded platforms e.g., NVIDIA Jetson or similar.
* Data Science experience.
* Experience using and managing large-scale HPC resources, e.g., Slurm, PBS, etc.
* Cloud development/deployment experience e.g., Docker and Kubernetes.
* Experience in data science methods and analysis.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, we want to hear from you.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression , sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
NVIDIA is a fabless semiconductor company providing graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip units (SoCs) for the mobile computing and automotive markets.