Solutions Architect, Data Science

Key Skills

Aartificial intelligence, C++, CUDA kernels, Data science techniques, High performance computing- HPC, IT, Machine learning techniques, Python Programming

Job Description

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.