Keysight Technologies

Manufactures test equipment and measurement software

Device Modeling AI/ML Software Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeSingaporeNo salary listedIn-person

About the Job

Requirements

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 is required.
At least 5 years of experience in software development for scientific, engineering, electronic design automation, or semiconductor applications is required.
Strong programming skills in Python and object-oriented software development are required.
Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn is required.
A solid understanding of data structures, algorithms, and software engineering principles is required.
Strong analytical, debugging, and problem-solving skills are required.
Experience developing software applications in a collaborative engineering environment is required.
Interest in applying artificial intelligence and machine learning technologies to semiconductor device modeling and electronic design automation is required.

Responsibilities

Design and develop artificial intelligence and machine-learning-driven solutions for semiconductor device characterization and compact model extraction workflows.
Develop software features for IC-CAP, WaferPro, Model Builder Program, Model Quality Assurance, 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 artificial-intelligence-powered characterization workflows.
Develop artificial-intelligence-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 artificial intelligence, agentic artificial intelligence, and large language model-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 research and development teams to define future artificial-intelligence-driven semiconductor modeling solutions.

Desired Qualifications

Experience with semiconductor devices, compact modeling, semiconductor physics, RF devices, analog/mixed-signal design, or electronic design automation technologies is preferred.
Familiarity with device characterization, parameter extraction, compact model development, SPICE modeling, or semiconductor measurement workflows is preferred.
Experience with surrogate modeling, Bayesian optimization, parameter estimation, machine-learning regression, anomaly detection, or predictive modeling techniques is preferred.
Familiarity with IC-CAP, WaferPro Express, Model Builder Program, Model Quality Assurance, TCAD, SPICE, or related semiconductor modeling tools is preferred.
Experience processing and analyzing large-scale characterization or measurement datasets is preferred.
Knowledge of artificial-intelligence-assisted engineering workflows, generative artificial intelligence, agentic artificial-intelligence systems, or large language model-based applications is preferred.
Experience with C++, Rust, or performance-oriented software development is preferred.
Experience developing software on Windows and Linux platforms is preferred.
Familiarity with Git, continuous integration and continuous delivery pipelines, and modern software development practices is preferred.
Experience with cloud computing, distributed computing, or scalable machine-learning infrastructure is preferred.
Interest in applying artificial intelligence and machine learning to accelerate semiconductor design and modeling workflows is preferred.

Overview

Keysight is at the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~16,800 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our award-winningculture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

At Keysight EDA, we are transforming semiconductor device modeling and characterization through the application of artificial intelligence, machine learning, and advanced software engineering. Our industry-leading products, including IC-CAP, WaferPro Express, Model Builder Program (MBP), and Model Quality Assurance (MQA), enable foundries, IDMs, and semiconductor companies worldwide to extract, validate, and deploy compact transistor models for advanced process technologies.

As a Device Modeling AI/ML Software Engineer, you will be responsible for developing intelligent software solutions that accelerate semiconductor characterization, compact model extraction, model validation, and device modeling workflows. You will work closely with software engineers, AI/ML experts, compact modeling specialists, and semiconductor domain experts to integrate next-generation AI technologies into Keysight's device modeling solutions.

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.***

About the Company

Keysight Technologies

Manufactures test equipment and measurement software

Keysight Technologies provides test and measurement equipment for electronics development and deployment. It sells high-precision hardware instruments (such as oscilloscopes, network analyzers, and signal generators) and software that support design, test, and validation of electronic systems, with focus areas including electronic design, e-mobility, network monitoring, and 5G. The products work by combining measurement hardware with analytics software to collect, analyze, and visualize test data across design, verification, and maintenance workflows. The company differentiates itself with a broad, industry-grade instrument portfolio, integrated end-to-end software, and ongoing services and support, including involvement in 6G development, to help speed digitalization and product deployment.

Company size: 10,001+
Company stage: IPO
Headquarters: Santa Rosa, CA
Founded: 1939

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