AI Enabled Device Modeling

Job Title

AI Enabled Device Modeling

Role Summary

Entry-level engineering role to develop AI/ML methods and reproducible workflows for semiconductor device modeling. Work combines device physics, measured silicon data, simulation (TCAD/compact models), and modern machine-learning techniques to accelerate parameter extraction, surrogate modeling, calibration, and prediction for CMOS and emerging devices.

Experience Level

Entry-level. Targeted at new college graduates (Bachelor's or Master's) or equivalent early-career candidates.

Responsibilities

The role develops, validates, and transitions AI-enabled device-modeling solutions and associated data workflows.

• Develop and evaluate ML methods for parameter extraction, surrogate modeling, model calibration, and device characteristic prediction.
• Build reproducible data pipelines combining measured device data, compact-model simulations, TCAD results, and process/test metadata.
• Train, validate, and compare models using holdout datasets, error metrics, uncertainty analysis, and physics-based constraints.
• Apply techniques such as neural networks, Gaussian processes, optimization, sensitivity analysis, and physics-informed ML.
• Automate model fitting, feature extraction, hyperparameter optimization, regression testing, visualization, and reporting using Python workflows.
• Collaborate with device, characterization, compact-modeling, PDK, EDA, and circuit-design teams to meet technical requirements.
• Document datasets, model architectures, training methods, validation results, limitations, and recommended usage for traceability.
• Contribute to proof-of-concept demonstrations and transition successful methods into maintainable workflows.
• Perform tasks in compliance with Environmental, Health, Safety & Security requirements.

Requirements

Must-have technical skills and experience; preferred items listed separately.

• Academic or project experience in machine learning, deep learning, statistical modeling, optimization, or scientific data analysis.
• Strong Python programming skills and experience with libraries such as NumPy, pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or JAX.
• Understanding of supervised learning, regression, neural networks, model validation, overfitting, uncertainty quantification, and quantitative performance evaluation.
• Foundational understanding of semiconductor device physics and transistor electrical behavior, with interest in AI applications to device modeling.
• Experience working with structured scientific or engineering datasets: data preparation, visualization, feature engineering, and reproducible analysis.
• Ability to communicate technical results clearly and collaborate across AI, device, modeling, characterization, and design teams.
• Willingness to travel up to 10% and fluency in written and verbal English.

Nice-to-have (preferred):

• Graduate coursework, thesis research, internship, co-op, or substantial project work in AI/ML for semiconductor devices, EDA, scientific ML, or computational physics.
• Experience with physics-informed neural networks, differentiable programming, Bayesian optimization, Gaussian processes, active learning, or uncertainty quantification.
• Exposure to compact transistor models, SPICE, parameter extraction, TCAD, cryogenic, photonic, superconducting devices, or quantum hardware.
• Experience with experiment tracking, version control, containers, MLflow, Weights & Biases, automated workflows, Linux, HPC, GPU acceleration, or cloud computing.
• Demonstrated initiative through publications, presentations, open-source contributions, competitions, or interdisciplinary research.
• Project management, planning, and organizational skills.

Education Requirements

Bachelor's or Master's degree (completed or expected) in Electrical Engineering, Computer Engineering, Computer Science, Data Science, Applied Physics, Physics, or a related field from an accredited program. Graduate coursework, thesis research, internships, or substantial project work in AI/ML for devices or related areas are listed as preferred.

About the Company

Company: GlobalFoundries

Headquarters: Saratoga Springs, New York, USA

GlobalFoundries is a leading contract manufacturer for the global semiconductor industry, with facilities in multiple countries, including the USA. The company develops a broad portfolio of semiconductor technologies and employs around 13,000 people worldwide. GlobalFoundries focuses on enhancing competitiveness in specialized application solutions and fostering innovation in mobile communications, consumer electronics, and automotive applications.