AI enabled Device Modeling Engineer
Core
Develop and deploy AI/ML methods to accelerate semiconductor device model extraction, improve predictive accuracy, and create scalable modeling workflows for CMOS, cryogenic, photonic, and superconducting devices.
Role type
Senior IC machine-learning engineer (semiconductor device modeling)
Builds
Production-relevant device models and scalable modeling workflows for semiconductor foundry customers
Domain
Semiconductor manufacturing / Computational physics / Machine Learning
Deliverable
production ML models
Required skills
Python, machine learning, semiconductor device physics, data pipeline construction, model validation, physics-informed ML, hyperparameter optimization
Preferred skills
Physics-informed neural networks, differentiable programming, Bayesian optimization, Gaussian processes, experiment tracking tools, high-performance computing
Technologies
PyTorch, TensorFlow, JAX, NumPy, pandas, SciPy, scikit-learn, Git, MLflow, Weights & Biases
Responsibilities
Develop and validate ML methods for parameter extraction and surrogate modeling; Build reproducible data pipelines combining measured data and TCAD results; Automate model fitting and reporting workflows; Collaborate with device and circuit design teams to translate requirements into modeling solutions.
Seniority
Senior, hands-on IC
