Keysight Technologies
From Keysight Technologies's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Here, you'll find opportunities to do your best work, take your career further, and thrive in an award-winning culture.
Overview
Keysight is a mission-critical design enablement partner for organizations solving the world’s most complex engineering challenges. With deep engineering expertise and leading design, emulation, and test solutions, our ~16,800 employees help customers in over 100 countries accelerate innovation across communications, automotive, energy, quantum, aerospace and defense, semiconductor, and artificial intelligence markets. Learn more about what we do.
At Keysight, people come together to explore new ideas, challenge what's possible, and advance the technologies defining the future. Here, you'll find opportunities to do your best work, take your career further, and thrive in an award-winning culture. Learn more about our benefits.
At Keysight EDA, we are advancing the next generation of semiconductor device modeling and characterization solutions used by leading foundries, IDMs, and semiconductor companies worldwide. Our products, including IC-CAP, WaferPro Express, Model Builder Program (MBP), and Model Quality Assurance (MQA), enable extraction, validation, and deployment of compact transistor models used in advanced process technologies.
As a Device Modeling AI/ML Software Intern, you will work with software engineers, device modeling experts, and AI researchers to develop intelligent workflows for semiconductor model extraction, parameter optimization, characterization data analysis, and model quality assessment. You will explore how machine learning, optimization, and AI-assisted automation can improve device modeling productivity and accuracy for advanced semiconductor technologies.
Assist in developing AI/ML solutions for semiconductor device characterization and compact model development
Contribute to intelligent parameter extraction and model fitting workflows
Support development of machine learning techniques for analyzing large-scale wafer measurement and characterization datasets
Explore AI-assisted approaches for model validation, quality assessment, and anomaly detection
Develop software components and data processing pipelines in Python
Build, train, and evaluate machine learning models for modeling and characterization workflows
Collaborate with domain experts working on IC-CAP, WaferPro, MBP, and MQA technologies
Participate in software design, code reviews, testing, and performance optimization activities
Investigate generative AI and agentic AI technologies to automate device modeling workflows and engineering productivity
Currently pursuing a Master's or PhD degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Physics, Semiconductor Engineering, EDA/CAD, Data Science, or a related technical field
Strong programming skills in Python
Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
Knowledge of data structures, algorithms, and object-oriented programming
Strong analytical and problem-solving skills
Interest in AI/ML applied to semiconductor technologies and engineering workflows
Coursework or research in semiconductor devices, compact modeling, RF devices, analog/mixed-signal circuits, semiconductor physics, or EDA/CAD
Familiarity with semiconductor characterization, parameter extraction, compact model development, or SPICE modeling concepts
Exposure to machine learning techniques for regression, optimization, surrogate modeling, anomaly detection, or predictive modeling
Familiarity with optimization, Bayesian optimization, parameter estimation, and design space exploration techniques
Experience analyzing large experimental or measurement datasets
Experience with C++, Rust, or performance-oriented software development
Exposure to software development on Windows or Linux platforms
Familiarity with Git and modern software development practices
Interest in AI-assisted device modeling, characterization automation, model quality assessment, and next-generation semiconductor design workflows
Curiosity and eagerness to work in an Agile, collaborative team environment
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
At Keysight EDA, we are advancing the next generation of semiconductor device modeling and characterization solutions used by leading foundries, IDMs, and semiconductor companies worldwide. Our products, including IC-CAP, WaferPro Express, Model Builder Program (MBP), and Model Quality Assurance (MQA), enable extraction, validation, and deployment of compact transistor models used in advanced process technologies.
As a Device Modeling AI/ML Software Intern, you will work with software engineers, device modeling experts, and AI researchers to develop intelligent workflows for semiconductor model extraction, parameter optimization, characterization data analysis, and model quality assessment. You will explore how machine learning, optimization, and AI-assisted automation can improve device modeling productivity and accuracy for advanced semiconductor technologies.
Assist in developing AI/ML solutions for semiconductor device characterization and compact model development
Contribute to intelligent parameter extraction and model fitting workflows
Support development of machine learning techniques for analyzing large-scale wafer measurement and characterization datasets
Explore AI-assisted approaches for model validation, quality assessment, and anomaly detection
Develop software components and data processing pipelines in Python
Build, train, and evaluate machine learning models for modeling and characterization workflows
Collaborate with domain experts working on IC-CAP, WaferPro, MBP, and MQA technologies
Participate in software design, code reviews, testing, and performance optimization activities
Investigate generative AI and agentic AI technologies to automate device modeling workflows and engineering productivity
Currently pursuing a Master's or PhD degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Physics, Semiconductor Engineering, EDA/CAD, Data Science, or a related technical field
Strong programming skills in Python
Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
Knowledge of data structures, algorithms, and object-oriented programming
Strong analytical and problem-solving skills
Interest in AI/ML applied to semiconductor technologies and engineering workflows
Coursework or research in semiconductor devices, compact modeling, RF devices, analog/mixed-signal circuits, semiconductor physics, or EDA/CAD
Familiarity with semiconductor characterization, parameter extraction, compact model development, or SPICE modeling concepts
Exposure to machine learning techniques for regression, optimization, surrogate modeling, anomaly detection, or predictive modeling
Familiarity with optimization, Bayesian optimization, parameter estimation, and design space exploration techniques
Experience analyzing large experimental or measurement datasets
Experience with C++, Rust, or performance-oriented software development
Exposure to software development on Windows or Linux platforms
Familiarity with Git and modern software development practices
Interest in AI-assisted device modeling, characterization automation, model quality assessment, and next-generation semiconductor design workflows
Curiosity and eagerness to work in an Agile, collaborative team environment
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
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