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NVIDIA

Senior Applications Engineer, AI for Material Science, Chemistry

NVIDIA

. Develop new tools and features in NVIDIA ALCHEMI for performant atomistic simulation workflows .

Posted 9/15/2026full-timeRemote • California • United StatesSenior💰 $168,000 - $322,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in developing high-performance numerical methods and material science applications, with proficiency in Fortran, C++, CUDA, and Python. Capable of integrating AI surrogates into atomistic simulation workflows and optimizing performance on large-scale HPC systems.

Highest-signal resume keywords
PhD In Computational PhysicsHigh Performance Numerical MethodsFortran ProgrammingCUDA ProgrammingMaterial Science Simulations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
C++ ProgrammingPython ProgrammingHigh Performance ComputingRuntime Performance OptimizationFloating Point EmulationMixed Precision LibrariesHigh Throughput ScreeningAlgorithm ImplementationScientific ComputingMaterial Science Tools
Soft Skills
Independent WorkCollaborationCommunication
Industry Keywords
Atomistic SimulationAI SurrogatesMaterial ScienceHPC SystemsPerformance Benchmarking

Tech Stack

Tools & technologies
PythonC++

About the role

Key responsibilities & impact
  • Develop new tools and features in NVIDIA ALCHEMI for performant atomistic simulation workflows
  • Guide customers or developers 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
  • Participate in workshops focused on material science and AI
  • Work across research, engineering, and product teams to build software tools bridging traditional simulations and AI surrogates

Requirements

What you’ll need
  • 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
  • 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

Benefits

Comp & perks
  • Competitive salaries
  • Generous benefits package
  • Equity