Solutions Architect, Data Science

NVIDIA’s Solution Architecture team is looking for a Data Science focused Solution Architect with expertise in Machine Learning (ML), Deep Learning (DL) and Data Science platforms. We work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinking about artificial intelligence, someone who can maintain constructive collaboration in a fast paced, rapidly evolving field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. You will be working with the latest HPC architecture coupled with the most advanced neural network models, changing the way people interact with technology.

As a Solutions Architect, you will be the first line of technical expertise between NVIDIA and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of partners and concerns.

What you’ll be doing:

• Develop HPC solutions using NVIDIA SDKs like Modulus and CUDA for physics simulations.

• Design GPU-accelerated workflows for complex simulations in optics, electromagnetics, and fluid dynamics.

• Deploy AI models for physics modeling and simulations.

• Support customers in leveraging NVIDIA platforms for physics modeling.

• Enhance NVIDIA's GPU capabilities in scientific computing applications.

• Apply NVIDIA Inference Microservices (NIM) to various domains, including language processing, computer vision, and scientific simulations.

What we need to see:

• Master's or Ph.D. in Electrical Engineering, Physics, Applied Mathematics, or related field.

• 5+ years in HPC, focusing on physics modeling and simulations.

• Sufficient experience in physics and GPU-accelerated frameworks.

• Proficient in Python; C++ and CUDA experience preferred.

• Expertise in numerical methods and computational physics.

Ways to stand out from the crowd:

• Experience with NVIDIA Modulus for physics-informed machine learning.

• Proficiency in NVIDIA tools for AI model deployment.

• Skill in optimizing physics simulations on NVIDIA GPUs.

• Background in simulation software for engineering applications.

• Ability to solve complex challenges in GPU-accelerated physics simulations.

• Familiarity with NIM for deploying and managing AI models.

At NVIDIA, we're tackling some of the most challenging computational problems in the industry, including those in advanced physics simulations and manufacturing processes. If you're passionate about leveraging GPU technology to revolutionize scientific computing and engineering simulations in these fields, we want to hear from you.

NVIDIA is an equal opportunity employer and values diversity in our workforce. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, national origin, disability status, age, or any other characteristic protected by law.