Senior HPC Performance Engineer - AI for Science at Scale

at Nvidia

USD 184,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 3 Algorithms CUDA @ 4 Communication @ 7 GPU HPC @ 4 JAX @ 6 Leadership @ 6 Machine Learning @ 6 Mathematics @ 7 Parallel Programming @ 7 PyTorch @ 6 Python @ 7 Technical Leadership @ 6

Details

NVIDIA is seeking a senior HPC performance engineer to join a team of scientists and engineers building the next generation of scientific machine learning frameworks. The role focuses on digital biology, high-performance computing, and machine learning methods to advance AI for Science.

Responsibilities

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

Requirements

Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, or Mathematics, or equivalent experience.
At least 5 years of relevant experience.
Consistent track record in performance engineering, software design, building and packaging, and launching software products, with a focus on acceleration.
Deep understanding of parallel programming in C++ and Python.
Programming experience with CUDA or OAI Triton.
Fluency in modern machine learning frameworks such as PyTorch, JAX, and Warp.
Experience applying HPC solutions to research problems in biology or chemistry, including atomistic simulations.
Technical leadership contributions, self-direction, and the ability to learn from and teach others.
Strong communication, organizational, self-motivation, and teamwork skills.

Preferred Qualifications

Contributions to major scientific AI for Science codebases with acceleration features such as new kernels.
Familiarity with pioneering language and geometric models used in AI for Science applications in biology and chemistry.

Benefits

Equity and benefits.
NVIDIA is an equal opportunity employer committed to a diverse work environment.
Applications will be accepted at least until February 21, 2026.