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NVIDIA

Designs the chips and software that power AI

Senior Application Engineer - HPC and AI for Physics

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A BS, MS, or PhD in computational, theoretical, and/or experimental physics, applied mathematics, or computer science, or equivalent experience.
  • At least 5 years of experience building HPC, AI, or machine learning software for applications in physics and numerical simulations.
  • Strong experience with GPU-accelerated computing and modern machine-learning frameworks.
  • Strong communication skills across technical and non-technical audiences.

Responsibilities

  • Develop workflows for experimental processing and analysis and numerical simulations applied to imaging science, plasma and high-energy physics, and materials science.
  • Profile applications and run benchmarks to identify bottlenecks, then provide recommendations to collaborators and product teams.
  • Build examples or sample applications for tutorials.
  • Represent NVIDIA at leading scientific conferences, workshops, and industry events.
  • Translate learnings from research collaborations into feedback for engineering on toolkits and libraries for accelerated super-resolution imaging, high-energy-density physics, plasma physics, and materials physics.

Desired Qualifications

  • High-impact publications in HPC and AI for numerical simulations, plasma physics, and imaging science.
  • Deep understanding of numerical simulations such as particle-in-cell.
  • Experience with CUDA, parallel programming, or performance-focused software development.
  • Familiarity with agentic AI workflows for science and discovery.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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