AI-Driven Semiconductor Device Modeling Engineer

Global Foundries; Town of Malta (NY); On-site; USD 58,000 - 101,000; Full time

Job summary

GlobalFoundries seeks a new graduate with strong AI/ML skills to develop AI-enabled methods for semiconductor device modeling. The engineer will combine device physics, measured silicon data, and modern ML techniques to accelerate model extraction and accuracy.

The role involves building reproducible data pipelines, training and validating ML models, and collaborating with device, PDK, and design teams to translate needs into scalable workflows. Travel up to 10% is expected.

Qualifications

• Bachelor's or Master's in Electrical/Computer Engineering, CS, Data Science, Applied Physics, or related field from an accredited program.
• Academic/project experience in machine learning, deep learning, statistical modeling, optimization, or scientific data analysis.
• Strong Python programming with libraries like NumPy, pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or JAX.
• Understanding of supervised learning, regression, neural networks, model validation, overfitting, uncertainty, and quantitative evaluation.
• Foundational semiconductor device physics knowledge with interest in AI-based device modeling.
• Experience with structured scientific datasets, data prep, visualization, feature engineering, and reproducible analysis.
• Ability to communicate results clearly and collaborate across AI, device, modeling, characterization, and design teams.
• Travel up to 10%.

Responsibilities

• Develop and evaluate ML methods for semiconductor device modeling, including parameter extraction and surrogate modeling.
• Build reproducible data pipelines combining measured device data, simulations, and process metadata.
• Train, validate, and compare AI/ML models with baselines, holdout sets, and uncertainty analysis.
• Apply neural networks, Gaussian processes, optimization, and physics-informed ML to device-modeling problems.
• Automate model fitting, feature extraction, hyperparameter tuning, regression testing, visualization, and reporting in Python workflows.
• Collaborate with device, characterization, and design teams to translate requirements into AI-enabled solutions.
• Document datasets, assumptions, model architecture, training, validation, limitations, and usage for traceability.

Skills

Python programming

ML/AI expertise

Data science

Model evaluation

Education

Bachelor's/Master's in EE/CE/CS/DS/Physics

Tools

NumPy

pandas

SciPy

scikit-learn

PyTorch

TensorFlow

JAX

Job description

GlobalFoundries seeks a new graduate with strong AI/ML skills to develop AI-enabled methods for semiconductor device modeling. The engineer will combine device physics, measured silicon data, and modern ML techniques to accelerate model extraction and accuracy.

The role involves building reproducible data pipelines, training and validating ML models, and collaborating with device, PDK, and design teams to translate needs into scalable workflows. Travel up to 10% is expected.