Senior AI Materials Engineer for Chemistry & Discovery

Socket.dev; Santa Clara (CA); On-site; USD 168,000 - 322,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA is seeking a Senior Application Engineer with a strong background in material science codes to accelerate AI-driven simulations for materials discovery. You will turn the latest research into software used by scientists, working across research, engineering, and product teams to build tools bridging traditional simulations and AI surrogates.

Required are a PhD or equivalent, 8+ years of high-performance numerical methods experience, and proficiency in Fortran, C++, CUDA, and Python.

Qualifications

• 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.

Responsibilities

• Collaborate with researchers and engineers to develop tools in NVIDIA ALCHEMI for performant atomistic simulation workflows.
• Guide customers on integrating material science applications with AI surrogates using NVIDIA ALCHEMI.
• Profile applications and run benchmarks to demonstrate product value.
• Collaborate with subject matter experts on whitepapers and research.
• Engage in workshops at the intersection of material science and AI.

Skills

Fortran

C++

CUDA

Python

Material Science tools

Education

PhD in computational physics/chemistry/CS or related

Job description

NVIDIA is seeking a Senior Application Engineer with a strong background in material science codes to accelerate AI-driven simulations for materials discovery. You will turn the latest research into software used by scientists, working across research, engineering, and product teams to build tools bridging traditional simulations and AI surrogates.

Required are a PhD or equivalent, 8+ years of high-performance numerical methods experience, and proficiency in Fortran, C++, CUDA, and Python.