Nvidia Solutions Architect - Deep Learning Drug Discovery 

United States, Texas 

74767028

What you will be doing:

• You will partner with our business / account team working with customers to develop a keen understanding of their goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs.

• Staying up on the state of the art in the production deep learning and machine learning methods. You'll be called on to help architect and scale high-performance, distributed, AI deployments that are built on the latest NVIDIA GPUsupercomputers.

• 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 customer on a whiteboard.

• Be an industry leader with vision on integrating NVIDIA technology into AI and HPC architectures for advanced applications, such as medical imaging or drug discovery.

• 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. You are empowered to find the best way to get your job done and make our customers successful.

What we need to see:

• MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry, Computational Physics, Chemical Engineering, Biophysics with strong applied experience in these domains.

• 5+ years of work-related experience in software development of deep learning or GPU acceleration methods for scientific applications.

• 3+ years of work-related experience with deep learning software architecture and frameworks or high performance computing applications.

• Proficient in the Linux/GNU toolchain and operating as a user in HPC cluster environments.

• Full-stack scientific computing experience including software development in scientific programming languages, such as Python, C/C++, and/or CUDA.

• Excellent communication skills particularly in the presentation of highly technical material. Must enjoy interacting with forward-thinking people, life-long learning, and staying at the forefront of the domain

Ways to stand out from the crowd:

• Demonstrated work in training and inference at scale and expertise in accelerated computing with GPU.

• Cloud platform expertise on AWS, Azure and/or GCP.
  Experience with genomics, virtual cells, or molecular dynamics is a plus

• Experience in the pharmaceutical industry or with customers/partners in the pharmaceutical domain is a plus.

• Published record of thought leadership in a technical area or industry segment.