AI Materials Research Engineer

Applied Materials • Santa Clara, CA

3d • $170,000 - $234,000 • Onsite

About The Position

Applied Materials is seeking an AI Materials Research Engineer to accelerate semiconductor materials discovery using Scientific AI, Computational Materials Science, and Machine Learning. The role combines materials science expertise with AI/ML, simulation, and data-driven modeling to develop next-generation materials and process innovations. Based on related internal Materials AI role descriptions.

Requirements

• MS/PhD in Materials Science, Computational Materials Science, Physics, Chemical Engineering, or related field.
• 2–5 years of experience in Computational Materials Science, Materials Informatics, Scientific ML, or AI for scientific applications.
• Strong Python programming and ML experience (PyTorch, TensorFlow, Scikit-Learn).
• Experience with one or more computational methods: DFT, MD, kMC, Phase-Field Modeling
• Strong understanding of: Crystal structures, Thermodynamics, Kinetics, Defect physics, Semiconductor materials

Nice To Haves

• Experience with simulation platforms such as VASP, Quantum Espresso, CP2K, LAMMPS, or GROMACS.
• Experience with Materials Project, OQMD, NOMAD, or similar databases.
• Familiarity with: Graph Neural Networks (GNNs), Materials Foundation Models, Physics-Informed ML, Generative AI for materials design
• Experience using cloud/HPC environments for large-scale model training and simulations.

Responsibilities

• Develop AI/ML models for: Materials property prediction, Materials screening and optimization, Process-performance modeling, Generative materials design
• Apply computational materials methodologies including: Density Functional Theory (DFT), Molecular Dynamics (MD), Kinetic Monte Carlo (kMC), Phase-field and Monte Carlo simulations
• Build AI surrogate models to accelerate simulation-driven research.
• Create materials informatics pipelines integrating: Experimental data, Characterization results, Simulation outputs, Scientific literature
• Develop AI copilots and agentic workflows for: Literature review, Hypothesis generation, Experiment planning, Simulation orchestration
• Collaborate with materials scientists, process engineers, and AI teams to deliver Scientific AI solutions.

Benefits

• Supportive work culture that encourages learning, development, and career growth.
• Empowerment to push boundaries and learn every day in a supportive leading global company.
• Programs and support that encourage personal and professional growth and care for employees at work, at home, or wherever they may go.
• Comprehensive benefits package
• Participation in a bonus program
• Stock award program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior