Applied ML Researcher (Force Fields and Simulation)
Core
Develop next-generation machine learning force fields and simulation infrastructure to accelerate the discovery of breakthrough materials for energy, clean water, and carbon capture.
Role type
Senior IC ML Research Engineer (Machine Learning Force Fields)
Builds
High-performance atomistic physics simulators and distributed ML training/inference systems
Domain
Materials science, computational chemistry, and AI
Deliverable
production ML models
Required skills
distributed machine learning systems, modern software engineering, computational methods, graph neural network design, high-performance computing
Preferred skills
Density Functional Theory, molecular simulation methods (MCMC, MD), cloud infrastructure, Kubernetes
Technologies
Ray, Kubernetes, DFT
Responsibilities
Train and fine-tune machine learning force fields, integrate models into high-performance simulators, develop active learning systems for data generation and training, collaborate with computational chemists on DFT data validation
Seniority
Senior, hands-on IC