AI Materials Research Engineer
Core
Accelerate semiconductor materials discovery using Scientific AI, Computational Materials Science, and Machine Learning to develop next-generation materials and process innovations.
Role type
Senior IC AI Materials Research Engineer
Builds
Production ML models for materials property prediction, screening, optimization, and generative design; AI surrogate models; agentic workflows for literature review and experiment planning.
Domain
Semiconductor industry + Computational Materials Science / Scientific AI
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Scikit-Learn, Density Functional Theory (DFT), Molecular Dynamics (MD), Kinetic Monte Carlo (kMC), Phase-field modeling, Crystal structures, Thermodynamics, Kinetics, Defect physics, Semiconductor materials
Preferred skills
VASP, Quantum Espresso, CP2K, LAMMPS, GROMACS, Materials Project, OQMD, NOMAD, Graph Neural Networks (GNNs), Materials Foundation Models, Physics-Informed ML, Generative AI for materials design, Cloud/HPC environments
Responsibilities
Develop AI/ML models for materials property prediction, screening, optimization, and generative design; Apply computational methodologies (DFT, MD, kMC, Phase-field); Build AI surrogate models to accelerate simulation-driven research; Create materials informatics pipelines integrating experimental data, characterization results, simulation outputs, and scientific literature; Develop AI copilots and agentic workflows for literature review, hypothesis generation, experiment planning, and simulation orchestration; Collaborate with materials scientists, process engineers, and AI teams to deliver Scientific AI solutions.
Seniority
Senior, hands-on IC
