Senior Machine Learning Engineer - Chemistry and Materials Science

Position Overview

NVIDIA is looking for a Senior Machine Learning Engineer to build AI frameworks that will solve toughest problems in science and engineering, including weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, and accelerated drug development. The role involves developing machine learning frameworks including NVIDIA PhysicsNeMo and ALCHEMI used by academic and industry partners to accelerate scientific discovery.

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

Requirements & Skills

• 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 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

• 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)