NVIDIA has become the platform upon which every new AI-powered application is built. We are seeking a Senior Machine Learning 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, we will enable powerful and efficient ML methods through collaborations with industry and academic partners. Together, we will advance NVIDIA’s capacity to accelerate AI for Science and industries that depend on it.
What you'll be doing:
Design performance and accuracy evaluation frameworks and carry out evaluations of pioneering ML models used in scientific discovery, in particular the ones relating to atomistic modeling. Identify end-to-end model execution bottlenecks, design and implement solutions at scale such as model parallelism.
Drive the testing and maintenance of the algorithms and software stack used in the AI for Science applications within the company and in the open source community
Stay up-to-date on the latest machine learning technologies and evaluate their potential as solutions to accuracy and/or computational performance bottlenecks.
Collaborate with multiple high performance computing, AI infrastructure, and research teams
Contribute to documentation or educational content relating to product
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 of performance engineering in large scale AI model training and inference applications, and deep understanding of compute bottlenecks of these models, and of paradigms of parallelism in these applications such as model parallelism.
Expertise in modern machine learning frameworks such as PyTorch, JAX, Warp and distributed learning strategies within them
Up-to-date knowledge of ML research in scientific discovery and in atomistic modeling
Experience with software design, building, packaging and launching software products based on ML research or atomistic simulation tools
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:
Contributor to major scientific codebase for atomistic modeling or AI for science
Experience with CUDA/Triton programming or familiarity with CUDA/Triton extensions of ML frameworks
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 have some of the most forward-thinking, resourceful and dedicated people in the world working with us and our engineering teams are growing fast in some of the hottest innovative fields: Quantum Computing, Artificial Intelligence, and Autonomous Vehicles. Are you a creative and autonomous engineer with a real passion for machine learning, computational biology and 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.
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.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
