Senior HPC Performance Engineer - AI for Science at Scale
at Nvidia
📍 Santa Clara, United States
$180,000-339,200 per year
SCRAPED
Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 7 Algorithms @ 4 Machine Learning @ 4 Data Science @ 4 TensorFlow @ 6 Leadership @ 4 Communication @ 7 Mathematics @ 7 Parallel Programming @ 7 Technical Leadership @ 4 PyTorch @ 6 CUDA @ 4Details
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.
Responsibilities
- Design and implement computationally performant features for large scale, CUDA-backed ML training frameworks, using low level acceleration and scaling strategies such as GPU porting, data structure innovations, distributed learning technologies.
- Optimize computational performance of a 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 generative machine learning models in digital biology and beyond.
- Collaborate with multiple HPC, AI infrastructure, and research teams.
- Develop tools to assist in data processing, data quality control, algorithm development, and algorithm testing.
- Drive the testing and maintenance of the algorithms and software modules.
Requirements
- Advanced degree in a quantitative field such as Computer Science, Computational Biophysics, Computational Chemistry, Physics, Mathematics, or equivalent experience.
- 8+ years of relevant experience.
- Consistent track record in performance engineering as well as software design, building, packaging, and launching software products.
- Deep understanding of parallel programming in C++, Python; ideally CUDA programming experience.
- Fluent in modern machine learning frameworks such as PyTorch, TensorFlow, JAX, Warp.
- Experience with HPC solutions to research problems, ideally for biology, chemistry, or material science applications.
- Recognized for technical leadership contributions, capable of self-direction, and ability to learn from and teach others.
- Strong communication skills, organized and self-motivated, and play well with others (be an excellent teammate!).
Ways to stand out from the crowd:
- Contributor to the major scientific AI for Science codebase.
- Familiarity with pioneering language and geometric models used in AI for Science applications in biology, chemistry, material science.
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.