AI-Driven Semiconductor Device Modeling Engineer

GlobalFoundries inc.; Essex Junction (VT); On-site; USD 58,000 - 101,000; Full time

Job summary

GlobalFoundries in the United States seeks a new graduate to develop AI-enabled methods for semiconductor device modeling. You will combine device physics with AI/ML techniques to accelerate model extraction and improve predictive accuracy across CMOS and other devices.

You will build reproducible data pipelines, train and validate models, and collaborate with device, PDK, and circuit-design teams to translate requirements into scalable modeling solutions, while documenting methods for

Qualifications

• Bachelor's or master's degree in a relevant field and coursework in ML/data science.
• Strong Python programming and scientific libraries experience.
• Experience with supervised learning, model validation, and uncertainty quantification.
• Exposure to semiconductor device physics and device modeling desired.

Responsibilities

• Develop and evaluate ML methods for semiconductor device modeling (parameter extraction, surrogate modeling, calibration).
• Build reproducible data pipelines combining measured data, simulations, and metadata.
• Train, validate, and compare ML models with baselines and physics-based constraints.
• Apply neural networks, Gaussian processes, optimization, and physics-informed ML.
• Automate model fitting, feature extraction, hyperparameter optimization, regression testing, visualization, and reporting using Python workflows.
• Collaborate with device, characterization, and design teams to deploy AI-enabled modeling solutions.
• Document datasets, assumptions, architecture, training, validation, and usage for traceability.
• Contribute to proof-of-concept demonstrations and transition to maintanable workflows.

Skills

Python

Machine learning

SciPy / NumPy / pandas

ML frameworks (PyTorch / TensorFlow /J

Gaussian processes

Education

Bachelor's or Master's in Electrical/Computer Engineering, CS, Data Science

Tools

Git

MLflow

Weights & Biases

Docker

CUDA / GPU acceleration

Job description

GlobalFoundries in the United States seeks a new graduate to develop AI-enabled methods for semiconductor device modeling. You will combine device physics with AI/ML techniques to accelerate model extraction and improve predictive accuracy across CMOS and other devices.

You will build reproducible data pipelines, train and validate models, and collaborate with device, PDK, and circuit-design teams to translate requirements into scalable modeling solutions, while documenting methods for