This role pays more than
67%
of similar roles. Most pay
$164,993–$235,750
— the shaded band above.
At the midpoint, this role pays about
$219k
versus about
$200k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
905 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 887 roles with salary data.
As a Senior Applications Engineer, AI for Material Science and Chemistry, you will join the team developing software tools to bridge traditional simulations and AI surrogates within the NVIDIA ALCHEMI ecosystem. You will translate research into functional software, collaborate with experts on whitepapers, and guide developers in integrating material science applications with AI surrogates. Your daily work involves building features for performant atomistic simulation workflows, profiling applications, and running benchmarks to demonstrate product value. The role requires expertise in computational physics or chemistry, high-performance numerical methods, and large-scale HPC systems. You will utilize a technical stack including Fortran, C++, CUDA, and Python, while applying knowledge of plane waves primitives, high-throughput screening, accelerator algorithm implementation, runtime performance optimization, floating point emulation, and mixed precision libraries to solve complex problems in the field of materials discovery.
Develop new tools and features in NVIDIA ALCHEMI to enable performant atomistic simulation workflows.
Translate recent research into functional software for scientists to use in material discovery.
Guide customers and developers on integrating material science applications with AI surrogates.
Profile applications and run benchmarks to demonstrate the product's value proposition.
Collaborate with subject matter experts to author whitepapers and technical research.
Participate in workshops focused on the intersection of material science and artificial intelligence.
Develop high-performance numerical methods for scientific computing and material science applications.
What we're looking for
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 running material science simulations on large scale HPC systems.
Proficiency in Fortran, C++, CUDA, Python, and common Material Science tools.
Outstanding knowledge of high-performance plane waves primitives response properties, high throughput screening (preferred).
Experience with high-performance accelerator algorithm implementation, runtime performance optimization, usage of floating point emulation, and mixed precision libraries (preferred).
CUDA
OpenCL
C
C++
Python
MPI
NVSHMEM
OpenSHMEM
IPC
Benchmarking
Profiling
Linear Algebra
Numerical Methods
High Performance Computing
Machine Learning
AI