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Senior HPC Performance Engineer - AI for Science at Scale

$184k - $287.5k

NVIDIA

NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Sr. HPC Performance engineer to join our team of scientists and engineers passionate about building the next generation of scientific machine learning (ML) frameworks. Starting with digital biology, through high performance computing (HPC) and powerful ML methods, together, we will advance NVIDIA’s capacity to accelerate AI for Science and industries that depend on it.

What you’ll be doing:

Design and implement computationally performant features for large scale, CUDA-backed ML training frameworks, using low level acceleration and scaling strategies such as kernel design, GPU porting, data structure innovations, distributed learning technologies Optimize computational performance of wide range of business-critical ML models via accelerated hardware and software stack, as well as algorithmic improvements Develop and maintain HPC software stack for atomistic modeling and generative machine learning in digital biology and beyond Collaborate with multiple HPC, AI infrastructure, and research teams Drive the testing and maintenance of the algorithms and software modules

What we need to see:

  • Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience
  • 5+ years of relevant experience
  • Consistent track record in performance engineering as well as software design, building and packaging and launching software products, with a focus on acceleration
  • Deep understanding of parallel programming in C++, Python; programming experience CUDA or OAI Triton
  • Fluent in modern machine learning frameworks such as PyTorch, JAX, Warp
  • Experience with HPC solutions to research problems for biology or chemistry, including but not limited to atomistic simulations
  • Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others
  • You should display strong communication skills, be organized and self-motivated, and play well with others (be an excellent teammate!)

Ways to stand out from the crowd:

  • Contribution to major scientific AI for Science codebase with acceleration features such as new kernels

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers.

We are an equal opportunity employer and value diversity at our company.

We have some of the most forward-thinking, resourceful and talented people in the world working with us and our engineering teams are growing fast in some of the hottest state-of-the-art fields: Digital Biology, Artificial Intelligence, and Autonomous Vehicles.

Are you a creative and autonomous engineer with a real passion for machine learning, computational chemistry, data science & parallel computing? If so, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

  • You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until February 21, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.

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Vacancy posted 11 hours ago
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