全职 Senior R-D Software Development Engineer 工作, 薪水, Keysight Technologies North Region (Singapore) 公司招聘中 - Ricebowl

• 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.

Job 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.