Responsibilities
Design, develop, test, and maintain software solutions for semiconductor device characterization, parameter extraction, compact model generation, and model validation.
Develop and enhance applications supporting device modeling platforms such as IC-CAP, MBP, WaferPro, MQA, and related EDA software.
Design and implement robust algorithms for numerical optimization, measurement data analysis, wafer-level automation, and scientific computing.
Develop scalable software, APIs, and automation workflows that improve performance, reliability, usability, and engineering productivity.
Design and integrate AI-assisted solutions, including machine learning and generative AI technologies, to automate engineering workflows, improve model extraction accuracy, and accelerate device modeling.
Collaborate with device modeling engineers and cross-functional teams to deliver innovative software solutions that meet customer and business requirements.
Follow Agile software development practices, participating in sprint planning, code reviews, testing, continuous integration, and iterative product delivery while ensuring high software quality.
Stay current with advances in semiconductor technologies, compact modeling methodologies, AI/ML, and modern software engineering practices, contributing to technical documentation and product releases.
Qualifications
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related technical field.
3+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.
Strong programming skills in C++ and/or Python, with experience in object-oriented software design and development.
Experience developing software involving numerical methods, optimization algorithms, data analysis, or mathematical modeling.
Familiarity with semiconductor device characterization, compact modeling, or EDA software development is highly desirable.
Experience with modern software development practices, including Git, automated testing, continuous integration, and Agile methodologies.
Solid understanding of machine learning algorithms, data preprocessing, and model validation. Experience with deep learning, neural networks, reinforcement learning, or generative AI technologies (e.g., LLMs) is a plus.
Strong analytical, problem-solving, and debugging skills, with the ability to innovate and solve complex challenges in device performance modeling.
Excellent written and verbal communication skills, with the ability to effectively communicate complex technical concepts to cross-functional teams.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Design, develop, test, and maintain software solutions for semiconductor device characterization, parameter extraction, compact model generation, and model validation.
Develop and enhance applications supporting device modeling platforms such as IC-CAP, MBP, WaferPro, MQA, and related EDA software.
Design and implement robust algorithms for numerical optimization, measurement data analysis, wafer-level automation, and scientific computing.
Develop scalable software, APIs, and automation workflows that improve performance, reliability, usability, and engineering productivity.
Design and integrate AI-assisted solutions, including machine learning and generative AI technologies, to automate engineering workflows, improve model extraction accuracy, and accelerate device modeling.
Collaborate with device modeling engineers and cross-functional teams to deliver innovative software solutions that meet customer and business requirements.
Follow Agile software development practices, participating in sprint planning, code reviews, testing, continuous integration, and iterative product delivery while ensuring high software quality.
Stay current with advances in semiconductor technologies, compact modeling methodologies, AI/ML, and modern software engineering practices, contributing to technical documentation and product releases.
Bachelor's or Master's degree in Computer Science, Electrical Engineering, Physics, Applied Mathematics, or a related technical field.
3+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.
Strong programming skills in C++ and/or Python, with experience in object-oriented software design and development.
Experience developing software involving numerical methods, optimization algorithms, data analysis, or mathematical modeling.
Familiarity with semiconductor device characterization, compact modeling, or EDA software development is highly desirable.
Experience with modern software development practices, including Git, automated testing, continuous integration, and Agile methodologies.
Solid understanding of machine learning algorithms, data preprocessing, and model validation. Experience with deep learning, neural networks, reinforcement learning, or generative AI technologies (e.g., LLMs) is a plus.
Strong analytical, problem-solving, and debugging skills, with the ability to innovate and solve complex challenges in device performance modeling.
Excellent written and verbal communication skills, with the ability to effectively communicate complex technical concepts to cross-functional teams.
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
