{"id":2256205,"url":"https://alion.io/job/keysight-device-modeling-aiml-software-engineer","title":"Device Modeling AI/ML Software Engineer","company":{"id":53596,"name":"Keysight","domain":"keysight.com","url":"https://alion.io/company/keysight","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":63000,"max_usd":133000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":26},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"C++","optional":true},{"name":"CI/CD","optional":true},{"name":"Git","optional":true},{"name":"Linux","optional":true},{"name":"Rust","optional":true},{"name":"Windows","optional":true}],"status":"live","first_seen_at":"2026-09-24T09:36:00Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-11T21:36:09Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"OverviewKeysight 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.\nOur award-winning culture 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.\nAt 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.\nAs 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.\nResponsibilities\nDesign and develop AI/ML-driven solutions for semiconductor device characterization and compact model extraction workflows\nDevelop software features for IC-CAP, WaferPro, MBP, MQA, and related device modeling products\nApply machine learning, optimization, and statistical modeling techniques to improve model extraction accuracy and productivity\nBuild scalable data processing, training, validation, and deployment pipelines for AI-powered characterization workflows\nDevelop AI-assisted solutions for parameter extraction, model calibration, quality assessment, and anomaly detection\nResearch and implement surrogate modeling techniques to reduce simulation and optimization turnaround time\nEvaluate and integrate generative AI, agentic AI, and LLM-based workflows to improve engineering productivity\nCollaborate with device modeling experts to develop solutions for advanced CMOS, RF, analog, power, and emerging semiconductor technologies\nContribute to software architecture, performance optimization, testing, code reviews, and product releases\nWork closely with global R&D teams to define future AI-driven semiconductor modeling solutions\nQualifications\nMaster's, or PhD degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Physics, Semiconductor Engineering, EDA/CAD, Data Science, or a related technical field\n5+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.\nStrong programming skills in Python and object-oriented software development\nExperience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn\nSolid understanding of data structures, algorithms, and software engineering principles\nStrong analytical, debugging, and problem-solving skills\nExperience developing software applications in a collaborative engineering environment\nInterest in applying AI/ML technologies to semiconductor device modeling and electronic design automation\nPreferred Qualifications\nExperience with semiconductor devices, compact modeling, semiconductor physics, RF devices, analog/mixed-signal design, or EDA technologies\nFamiliarity with device characterization, parameter extraction, compact model development, SPICE modeling, or semiconductor measurement workflows\nExperience with surrogate modeling, Bayesian optimization, parameter estimation, machine learning regression, anomaly detection, or predictive modeling techniques\nFamiliarity with IC-CAP, WaferPro Express, MBP, MQA, TCAD, SPICE, or related semiconductor modeling tools\nExperience processing and analyzing large-scale characterization or measurement datasets\nKnowledge of AI-assisted engineering workflows, generative AI, agentic AI systems, or LLM-based applications\nExperience with C++, Rust, or performance-oriented software development\nExperience developing software on Windows and Linux platforms\nFamiliarity with Git, CI/CD pipelines, and modern software development practices\nExperience with cloud computing, distributed computing, or scalable ML infrastructure\nPassion for applying AI and machine learning to accelerate semiconductor design and modeling workflows\nCareers Privacy Statement ***Keysight is an Equal Opportunity Employer.***\nDesign and develop AI/ML-driven solutions for semiconductor device characterization and compact model extraction workflows\nDevelop software features for IC-CAP, WaferPro, MBP, MQA, and related device modeling products\nApply machine learning, optimization, and statistical modeling techniques to improve model extraction accuracy and productivity\nBuild scalable data processing, training, validation, and deployment pipelines for AI-powered characterization workflows\nDevelop AI-assisted solutions for parameter extraction, model calibration, quality assessment, and anomaly detection\nResearch and implement surrogate modeling techniques to reduce simulation and optimization turnaround time\nEvaluate and integrate generative AI, agentic AI, and LLM-based workflows to improve engineering productivity\nCollaborate with device modeling experts to develop solutions for advanced CMOS, RF, analog, power, and emerging semiconductor technologies\nContribute to software architecture, performance optimization, testing, code reviews, and product releases\nWork closely with global R&D teams to define future AI-driven semiconductor modeling solutions\nMaster's, or PhD degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Physics, Semiconductor Engineering, EDA/CAD, Data Science, or a related technical field\n5+ years of experience in software development for scientific, engineering, EDA, or semiconductor applications.\nStrong programming skills in Python and object-oriented software development\nExperience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn\nSolid understanding of data structures, algorithms, and software engineering principles\nStrong analytical, debugging, and problem-solving skills\nExperience developing software applications in a collaborative engineering environment\nInterest in applying AI/ML technologies to semiconductor device modeling and electronic design automation\nPreferred Qualifications\nExperience with semiconductor devices, compact modeling, semiconductor physics, RF devices, analog/mixed-signal design, or EDA technologies\nFamiliarity with device characterization, parameter extraction, compact model development, SPICE modeling, or semiconductor measurement workflows\nExperience with surrogate modeling, Bayesian optimization, parameter estimation, machine learning regression, anomaly detection, or predictive modeling techniques\nFamiliarity with IC-CAP, WaferPro Express, MBP, MQA, TCAD, SPICE, or related semiconductor modeling tools\nExperience processing and analyzing large-scale characterization or measurement datasets\nKnowledge of AI-assisted engineering workflows, generative AI, agentic AI systems, or LLM-based applications\nExperience with C++, Rust, or performance-oriented software development\nExperience developing software on Windows and Linux platforms\nFamiliarity with Git, CI/CD pipelines, and modern software development practices\nExperience with cloud computing, distributed computing, or scalable ML infrastructure\nPassion for applying AI and machine learning to accelerate semiconductor design and modeling workflows\nCareers Privacy Statement ***Keysight is an Equal Opportunity 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