Senior Machine Learning Engineer - Chemistry and Materials Science

NVIDIA•Santa Clara, CA

About The Position

NVIDIA’s deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate and creative people to help us on building AI frameworks that will solve the toughest and most relevant problems of humanity and problems that are at the cutting edge of science & engineering: weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, etc. What you'll be doing: Work with some of the brightest minds in a leading AI company to develop leading machine learning frameworks including NVIDIA PhysicsNeMo and ALCHEMI used by our academic and industry partners to accelerate scientific discovery and solve real world problems at scale Work with internal project teams to validate applications built using the framework across NVIDIA's products Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies that couple physical simulations with AI/ML models What we need to see: BS or MS degree (PhD preferred) in computer science, mathematics, computational chemistry/materials science, physical chemistry or related technical field or equivalent experience 5+ yrs of relevant experience Strong Python programming skills Familiarity with containers, continuous integration/continuous development, numeric libraries, modular software design, and collaborative programming/engineering Good understanding and intuition for state-of-the-art AI/ML architectures and techniques including but not limited to geometric deep learning, Euclidean neural networks, diffusion/flow matching Familiarity across the AI framework ecosystem: e.g. PyTorch, PyTorch Geometric, Jax, Flax Experience across the AI/ML model lifecycle: from dataset curation,from dataset curation to training techniques, to inference deployment and performance optimization Proven track record of applying AI/ML techniques to solve real world problems in chemistry and materials science: e.g. surrogate interatomic potentials, inverse design, crystal structure prediction, experimental characterization Strong analytical skills with bias for action.Good time management and organization skills to thrive in a fast paced, dynamic environment Solid written and oral communications skills. Good teamwork and interpersonal skills Ways to stand out from the crowd: Work with distributed systems with data-parallel and model parallel programming experience. Experience with CUDA Python. Experience working with GPU (SIMT/Tile) parallelism Published papers in the field of AI with chemistry and materials science applications. Presentations at major workshops and conferences; NeurIPS, ICLR, ICML Familiarity with accelerated simulation packages in quantum chemistry (e.g. PySCF, VASP) and/or molecular dynamics (e.g. LAMMPS, OpenMM) NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! 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 deep learning — 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, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until February 9, 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. #deeplearning NVIDIA is the world leader in accelerated computing. NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Learn more about NVIDIA.

Requirements

BS or MS degree (PhD preferred) in computer science, mathematics, computational chemistry/materials science, physical chemistry or related technical field or equivalent experience
5+ yrs of relevant experience
Strong Python programming skills
Familiarity with containers, continuous integration/continuous development, numeric libraries, modular software design, and collaborative programming/engineering
Good understanding and intuition for state-of-the-art AI/ML architectures and techniques including but not limited to geometric deep learning, Euclidean neural networks, diffusion/flow matching
Familiarity across the AI framework ecosystem: e.g. PyTorch, PyTorch Geometric, Jax, Flax
Experience across the AI/ML model lifecycle: from dataset curation,from dataset curation to training techniques, to inference deployment and performance optimization
Proven track record of applying AI/ML techniques to solve real world problems in chemistry and materials science: e.g. surrogate interatomic potentials, inverse design, crystal structure prediction, experimental characterization
Strong analytical skills with bias for action.
Good time management and organization skills to thrive in a fast paced, dynamic environment
Solid written and oral communications skills.
Good teamwork and interpersonal skills

Nice To Haves

Work with distributed systems with data-parallel and model parallel programming experience.
Experience with CUDA Python.
Experience working with GPU (SIMT/Tile) parallelism
Published papers in the field of AI with chemistry and materials science applications.
Presentations at major workshops and conferences; NeurIPS, ICLR, ICML
Familiarity with accelerated simulation packages in quantum chemistry (e.g. PySCF, VASP) and/or molecular dynamics (e.g. LAMMPS, OpenMM)

Responsibilities

Work with some of the brightest minds in a leading AI company to develop leading machine learning frameworks including NVIDIA PhysicsNeMo and ALCHEMI used by our academic and industry partners to accelerate scientific discovery and solve real world problems at scale
Work with internal project teams to validate applications built using the framework across NVIDIA's products
Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies that couple physical simulations with AI/ML models