About the job
We are building the software infrastructure for the next era of scientific discovery. At NVIDIA, we believe AI will transform how new chemicals and materials are discovered. We are developing the software tools to make that possible! NVIDIA ALCHEMI is a key pillar of this stack, and this role will help shape ALCHEMI and the broader software ecosystem around it.
We are looking for a senior application engineer with background in material science codes to accelerate AI-driven simulations for materials discovery. You will turn the latest research into software that scientists use for real discovery. You will work across research, engineering, and product teams in building software tools for materials science and chemistry bridging traditional simulations and AI surrogates.
Responsibilities
Collaborate with some of the brightest minds in computational chemistry and AI to develop new tools and features in NVIDIA ALCHEMI to enable developers and researchers with performant atomistic simulation workflows.
Work directly with a customer or developer, guiding them how to integrate material science applications with AI surrogates using NVIDIA ALCHEMI into their workflows.
Profile the application and run benchmarks to show the product’s value proposition.
Collaborate with subject matter experts on whitepapers and research.
Engage and participate in workshops focussed on the intersection of material science and AI.
Qualifications
Minimum
PhD or equivalent experience in computational physics, computational chemistry, computer science, or related technical fields
8+ years of experience or demonstrable expertise in developing high performance numerical methods for scientific computing or material science applications
Experience in running material science simulations on large scale HPC systems
Ability to work independently and as part of a globally distributed team.
Proficiency in Fortran, C++, CUDA, Python and common Material Science tools
Preferred
Outstanding knowledge of high-performance plane waves primitives response properties, high throughput screening,
Experience with high-performance accelerator algorithm implementation, runtime performance optimization, usage of floating point emulation, and mixed precision libraries.