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Open nowPosted 29 days ago

Senior R&D Software Development Engineer

MyCareersFuture94,028 open roles

Pay
SGD 7,965 – SGD 10,700 a month
Where
North, Singapore
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Your applicationOpen nowSenior R&D Software Development EngineerMyCareersFuture · North, Singapore

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  5. 33.7%30 days
This job: posted 29 days ago

The posting

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-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.

We are seeking an innovative R&D Software Engineer to develop next-generation software solutions for semiconductor device characterization, parameter extraction, compact model generation, and AI-assisted engineering automation. The successful candidate will contribute to advanced modeling platforms such as IC-CAP, MBP, WaferPro, and MQA while leveraging modern software engineering and artificial intelligence technologies to improve productivity, accuracy, and workflow automation.

This role involves close collaboration with device modeling engineers, application engineers, and semiconductor technology experts to deliver high-performance software solutions for advanced silicon, compound semiconductor, RF, and power devices.

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.
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