{"schemaVersion":"jobsearcher.job.v1","id":"59afc1d33a574e33a192ec22","url":"https://jobsearcher.com/jobs/59afc1d33a574e33a192ec22","canonicalUrl":"https://jobsearcher.com/jobs/59afc1d33a574e33a192ec22","title":"R&D Engineering, Staff Engineer","description":"We Are\nSynopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.\nYou Are\nAn innovative and driven software engineer with a solid foundation in C++ and object-oriented programming. You have a passion for solving complex problems and a keen interest in exploring cutting-edge solutions. Debugging is not a chore for you; it is a puzzle you enjoy solving.\nYou are drawn to problems that sit at the intersection of physics, mathematics, and software. Parasitic extraction, capacitance modeling, algorithmic optimization, these are not abstract concepts to you. You do not need someone to hand you a perfect spec. You talk to domain experts, ask the right questions, and figure out what needs to be built.\nMachine learning and optimization techniques interest you not because they are trendy, but because they might solve the problem better. At Synopsys, you will work on StarRC, the tool that sets the standard for parasitic extraction in the semiconductor industry. What you build will directly enable the next generation of chips.\nWhat You'll Be Doing\nDesign, develop, and maintain core components of StarRC, the industry gold standard parasitic extraction tool used across leading semiconductor companies\nBuild and refine capacitance models that enable accurate extraction for advanced technology nodes, often before the competition catches up\nDevelop next-generation parasitic extraction algorithms focused on runtime reduction, memory efficiency, and capacity improvements for increasingly complex designs\nWrite and enhance Python or Tcl scripts to analyze large datasets, identify performance bottlenecks, and apply machine learning techniques to optimize extraction flows\nCollaborate directly with domain experts in electromagnetics, circuit modeling, and verification to solve tough technical problems that span multiple disciplines\nDebug complex issues in a large C++ codebase, trace problems across modules, and deliver fixes that improve tool stability and accuracy\nThe Impact You Will Have\nKeep StarRC at the leading edge of parasitic extraction technology, directly influencing how the world's most advanced chips are designed\nEnable semiconductor companies to adopt new process technologies faster by delivering accurate models and extraction flows ahead of industry timelines\nReduce customer runtime and memory usage by double-digit percentages, translating to real cost savings and faster design cycles for chips powering AI, automotive, and mobile devices\nPush the boundaries of what is possible in EDA by integrating machine learning and optimization techniques into production-grade extraction tools\nImprove the reliability and accuracy of a tool that thousands of engineers depend on daily for tape out-critical work\nShape the future of electronics by contributing to the software infrastructure that makes next-generation semiconductor design feasible\nWhat You'll Need\nMS with at least 3 years of software development experience, or PhD with focused research in algorithms, numerical methods, or related areas. Doctorate or equivalent industry depth is preferred\nStrong C++ programming skills with experience building and debugging performance-critical software in large codebases\nSolid understanding of data structures, algorithms, and software development processes including version control, testing, and code review\nExperience working in a Linux environment and comfort with scripting languages like Python, Tcl, or Perl for automation and analysis\nBackground in numerical mathematics, optimization, machine learning, or computational electromagnetics is a strong plus, especially as applied to EDA or physical modeling problems\nWho You Are\nA proactive and collaborative team player\nDetail-oriented with strong problem-solving skills\nPassionate about learning and applying new technologies\nEffective communicator with the ability to convey complex technical concepts clearly\nAdaptable and able to thrive in a fast-paced, dynamic environment\n\nThe Team You'll Be Part Of\nYou will join a high-performing R&D team dedicated to advancing StarRC, the market-leading interconnect parasitic extraction tool. The team is composed of domain experts in electromagnetics, algorithm development, and software engineering who work collaboratively to tackle complex technical challenges. You will be working closely with both local and global team members, contributing to a tool that is critical to semiconductor design flows worldwide. The environment is technical, supportive, and focused on continuous improvement.\nRewards and Benefits\nWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.\n#LI-DP1\n#TPG","company":"Synopsys","rawCompany":"synopsys","city":"Sunnyvale","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-03T16:26:18.019Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"17-2072.00","title":"Electronics Engineers, Except Computer","slug":"electronics-engineers-except-computer"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"334413","title":"Semiconductor and Related Device Manufacturing","slug":"semiconductor-and-related-device-manufacturing"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"R&D Engineering, Staff Engineer","description":"We Are\nSynopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow.\nYou Are\nAn innovative and driven software engineer with a solid foundation in C++ and object-oriented programming. You have a passion for solving complex problems and a keen interest in exploring cutting-edge solutions. Debugging is not a chore for you; it is a puzzle you enjoy solving.\nYou are drawn to problems that sit at the intersection of physics, mathematics, and software. Parasitic extraction, capacitance modeling, algorithmic optimization, these are not abstract concepts to you. You do not need someone to hand you a perfect spec. You talk to domain experts, ask the right questions, and figure out what needs to be built.\nMachine learning and optimization techniques interest you not because they are trendy, but because they might solve the problem better. At Synopsys, you will work on StarRC, the tool that sets the standard for parasitic extraction in the semiconductor industry. What you build will directly enable the next generation of chips.\nWhat You'll Be Doing\nDesign, develop, and maintain core components of StarRC, the industry gold standard parasitic extraction tool used across leading semiconductor companies\nBuild and refine capacitance models that enable accurate extraction for advanced technology nodes, often before the competition catches up\nDevelop next-generation parasitic extraction algorithms focused on runtime reduction, memory efficiency, and capacity improvements for increasingly complex designs\nWrite and enhance Python or Tcl scripts to analyze large datasets, identify performance bottlenecks, and apply machine learning techniques to optimize extraction flows\nCollaborate directly with domain experts in electromagnetics, circuit modeling, and verification to solve tough technical problems that span multiple disciplines\nDebug complex issues in a large C++ codebase, trace problems across modules, and deliver fixes that improve tool stability and accuracy\nThe Impact You Will Have\nKeep StarRC at the leading edge of parasitic extraction technology, directly influencing how the world's most advanced chips are designed\nEnable semiconductor companies to adopt new process technologies faster by delivering accurate models and extraction flows ahead of industry timelines\nReduce customer runtime and memory usage by double-digit percentages, translating to real cost savings and faster design cycles for chips powering AI, automotive, and mobile devices\nPush the boundaries of what is possible in EDA by integrating machine learning and optimization techniques into production-grade extraction tools\nImprove the reliability and accuracy of a tool that thousands of engineers depend on daily for tape out-critical work\nShape the future of electronics by contributing to the software infrastructure that makes next-generation semiconductor design feasible\nWhat You'll Need\nMS with at least 3 years of software development experience, or PhD with focused research in algorithms, numerical methods, or related areas. Doctorate or equivalent industry depth is preferred\nStrong C++ programming skills with experience building and debugging performance-critical software in large codebases\nSolid understanding of data structures, algorithms, and software development processes including version control, testing, and code review\nExperience working in a Linux environment and comfort with scripting languages like Python, Tcl, or Perl for automation and analysis\nBackground in numerical mathematics, optimization, machine learning, or computational electromagnetics is a strong plus, especially as applied to EDA or physical modeling problems\nWho You Are\nA proactive and collaborative team player\nDetail-oriented with strong problem-solving skills\nPassionate about learning and applying new technologies\nEffective communicator with the ability to convey complex technical concepts clearly\nAdaptable and able to thrive in a fast-paced, dynamic environment\n\nThe Team You'll Be Part Of\nYou will join a high-performing R&D team dedicated to advancing StarRC, the market-leading interconnect parasitic extraction tool. The team is composed of domain experts in electromagnetics, algorithm development, and software engineering who work collaboratively to tackle complex technical challenges. You will be working closely with both local and global team members, contributing to a tool that is critical to semiconductor design flows worldwide. The environment is technical, supportive, and focused on continuous improvement.\nRewards and Benefits\nWe offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.\n#LI-DP1\n#TPG","datePosted":"2026-08-03T16:26:18.019Z","dateModified":"2026-08-03T16:26:18.019Z","hiringOrganization":{"@type":"Organization","name":"Synopsys","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sunnyvale","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"59afc1d33a574e33a192ec22"},"url":"https://jobsearcher.com/jobs/59afc1d33a574e33a192ec22"}}