Responsibilities
Design and develop AI/ML-driven solutions for semiconductor device characterization and compact model extraction workflows
Develop software features for IC-CAP, WaferPro, MBP, MQA, and related device modeling products
Apply machine learning, optimization, and statistical modeling techniques to improve model extraction accuracy and productivity
Build scalable data processing, training, validation, and deployment pipelines for AI-powered characterization workflows
Develop AI-assisted solutions for parameter extraction, model calibration, quality assessment, and anomaly detection
Research and implement surrogate modeling techniques to reduce simulation and optimization turnaround time
Evaluate and integrate generative AI, agentic AI, and LLM-based workflows to improve engineering productivity
Collaborate with device modeling experts to develop solutions for advanced CMOS, RF, analog, power, and emerging semiconductor technologies
Contribute to software architecture, performance optimization, testing, code reviews, and product releases
Work closely with global R&D teams to define future AI-driven semiconductor modeling solutions
Qualifications
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
5+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.
Strong programming skills in Python and object-oriented software development
Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
Solid understanding of data structures, algorithms, and software engineering principles
Strong analytical, debugging, and problem-solving skills
Experience developing software applications in a collaborative engineering environment
Interest in applying AI/ML technologies to semiconductor device modeling and electronic design automation
Preferred Qualifications
Experience with semiconductor devices, compact modeling, semiconductor physics, RF devices, analog/mixed-signal design, or EDA technologies
Familiarity with device characterization, parameter extraction, compact model development, SPICE modeling, or semiconductor measurement workflows
Experience with surrogate modeling, Bayesian optimization, parameter estimation, machine learning regression, anomaly detection, or predictive modeling techniques
Familiarity with IC-CAP, WaferPro Express, MBP, MQA, TCAD, SPICE, or related semiconductor modeling tools
Experience processing and analyzing large-scale characterization or measurement datasets
Knowledge of AI-assisted engineering workflows, generative AI, agentic AI systems, or LLM-based applications
Experience with C++, Rust, or performance-oriented software development
Experience developing software on Windows and Linux platforms
Familiarity with Git, CI/CD pipelines, and modern software development practices
Experience with cloud computing, distributed computing, or scalable ML infrastructure
Passion for applying AI and machine learning to accelerate semiconductor design and modeling workflows
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
Design and develop AI/ML-driven solutions for semiconductor device characterization and compact model extraction workflows
Develop software features for IC-CAP, WaferPro, MBP, MQA, and related device modeling products
Apply machine learning, optimization, and statistical modeling techniques to improve model extraction accuracy and productivity
Build scalable data processing, training, validation, and deployment pipelines for AI-powered characterization workflows
Develop AI-assisted solutions for parameter extraction, model calibration, quality assessment, and anomaly detection
Research and implement surrogate modeling techniques to reduce simulation and optimization turnaround time
Evaluate and integrate generative AI, agentic AI, and LLM-based workflows to improve engineering productivity
Collaborate with device modeling experts to develop solutions for advanced CMOS, RF, analog, power, and emerging semiconductor technologies
Contribute to software architecture, performance optimization, testing, code reviews, and product releases
Work closely with global R&D teams to define future AI-driven semiconductor modeling solutions
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
5+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.
Strong programming skills in Python and object-oriented software development
Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn
Solid understanding of data structures, algorithms, and software engineering principles
Strong analytical, debugging, and problem-solving skills
Experience developing software applications in a collaborative engineering environment
Interest in applying AI/ML technologies to semiconductor device modeling and electronic design automation
Preferred Qualifications
Experience with semiconductor devices, compact modeling, semiconductor physics, RF devices, analog/mixed-signal design, or EDA technologies
Familiarity with device characterization, parameter extraction, compact model development, SPICE modeling, or semiconductor measurement workflows
Experience with surrogate modeling, Bayesian optimization, parameter estimation, machine learning regression, anomaly detection, or predictive modeling techniques
Familiarity with IC-CAP, WaferPro Express, MBP, MQA, TCAD, SPICE, or related semiconductor modeling tools
Experience processing and analyzing large-scale characterization or measurement datasets
Knowledge of AI-assisted engineering workflows, generative AI, agentic AI systems, or LLM-based applications
Experience with C++, Rust, or performance-oriented software development
Experience developing software on Windows and Linux platforms
Familiarity with Git, CI/CD pipelines, and modern software development practices
Experience with cloud computing, distributed computing, or scalable ML infrastructure
Passion for applying AI and machine learning to accelerate semiconductor design and modeling workflows
Careers Privacy Statement***Keysight is an Equal Opportunity Employer.***
