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Senior Product Manager, HPC and AI for Physics

NVIDIA Corporation

US, CA, Remote, US, MA, RemoteRemotePosted Aug 25, 2026
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HPC and AI can reshape the Exabytes data processing/analysis, development of high energy density physics simulations, and discovery of resilient materials across various industries ranging from supercomputing, higher education, clean energy, manufacturing, semiconductors, etc. We are looking for a Senior Product Manager who will drive the development of product and capabilities that combine HPC and AI/ML techniques to accelerate the discovery and design of plasma and high energy physics including resilient materials, numerical simulations, etc. We’re seeking someone who is a self-starter with demonstrated experience in developing products from the ground up. Are you passionate about groundbreaking technology? If so, we would love to learn more about you! What you will be doing: • Define the product features, capabilities, value proposition, positioning, and roadmap based on market analysis and customer feedback. • Work closely with engineering to set requirements, priorities and drive integration with complementary NVIDIA software products. • Define go-to-market strategy and build assets for product launches, blogs, webinars, PR, and sales enablement. • Stay up-to-date with the latest trends and offerings to identify early-access customers and partnership opportunities • Participate and present in workshops and conferences What we need to see: • Degree in Physics, Applied Math, Computer Science (Ph.D. preferred) or equivalent experience • Experience and familiarity with applied physics and material science simulation tools, AI and scientific computing applications • 7+ years in a technical product leadership role in delivering software and libraries • Proven record of collaborating in a matrix organization • Entrepreneurial spirit with strong communication skills to articulate the value proposition to technical and non-technical audiences Ways to stand out from the crowd: • Background in developing high energy, plasma physics simulation software packages, fusion materials and blanket design, or numerical and data processing/analysis for physics/material science/plasma science. • Good understanding of modern processor technologies (GPUs preferred) as applied to scientific computing • Hands-on demeanor for problem solving and building customer friendly products With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative, entrepreneurial and autonomous with a real passion for technology, we want to hear from you. #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 258,750 USD for Level 4, and 208,000 USD - 327,750 USD for Level 5. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 29, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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