Date posted 08/11/2026
Synopsys 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.
You have an electrical or electronics engineering background and you are ready to what you learned in a real R&D lab environment. You are comfortable with test equipment like oscilloscopes and signal analyzers, whether from university projects, internships, or early career work, and you want to go deeper. Writing scripts to automate repetitive tasks makes sense to you, and you are eager to learn how to build tools that make validation faster and more reliable.
You can read a schematic and understand signal flow well enough to set up a test or troubleshoot when measurements do not match expectations. Debugging does not frustrate you, it engages you. You like figuring out why something behaves a certain way, and you are willing to dig through data, documentation, and hardware until you find the answer. You are curious about how AI and machine learning can be applied to engineering problems, even if your experience so far is academic or exploratory.
At Synopsys, you will work alongside experienced hardware engineers and designers in a lab equipped with professional-grade instrumentation, and you will have the opportunity to develop automation, data analysis, and problem-solving skills that will define your engineering career.
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Build and maintain test automation scripts that execute validation sequences, collect measurement data, and flag issues automatically
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Analyze validation data to identify trends, performance characteristics, and anomalies that help the team understand hardware behavior
Learn to- AI and machine learning techniques to improve how the team processes and interprets large datasets from test campaigns
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Debug hardware issues using lab instrumentation like oscilloscopes, network analyzers, and spectrum analyzers to understand system and component-level behavior
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Maintain the database infrastructure required to support the collection of data
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Set up and document test configurations, including instrumentation connections, board-level integration, and validation procedures
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Organize and report test results in a clear, structured format that engineering teams can use to make design decisions
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Contribute to continuous improvement of test processes, automation tools, and lab workflows
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Your automation work will reduce the time engineers spend on repetitive test execution, allowing the team to validate more configurations in less time
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The data analysis you perform will help surface issues earlier in the development cycle, improving product quality and reducing costly redesigns
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Your contributions to AI-enabled tooling will help the team extract meaningful insights from test data faster than manual review allows
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The test setups and documentation you create will support validation efforts across multiple projects and product lines
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Your debugging efforts will help resolve hardware issues that could otherwise delay product schedules
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The process improvements you help implement will raise the overall efficiency and effectiveness of the validation team
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Your work will contribute directly to the quality and reliability of Synopsys hardware and IP products that customers integrate into their semiconductor designs
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Bachelor's or Master's degree in Electrical Engineering, Electronic Engineering, or a related technical field
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Hands-on experience with electronic test equipment such as oscilloscopes, signal generators, or network analyzers, whether from coursework, internships, or professional work
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Ability to read and interpret board schematics and electronic component functions
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Programming or scripting experience in languages like Python, MATLAB, or similar tools used for data processing or automation
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Strong organizational skills and attention to detail when managing test data, documentation, and multiple validation tasks
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Good communication skills and the ability to explain technical findings to other engineers clearly
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Experience with data analysis libraries in Python (Pandas, NumPy) or exposure to machine learning
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Experience in Digital Design with either Verilog or VHDL is a plus
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You can look at test results that do not match expectations and start forming ideas about what might be wrong and how to investigate further
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When you encounter a problem you have not seen before, you use available resources including documentation, schematics, and more experienced engineers to work toward a solution
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You write code and scripts that are organized and documented well enough that you or someone else can understand and modify them later
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You can explain a technical issue or test result to a colleague in a way that is clear and accurate without unnecessary complexity
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You are comfortable asking questions when you need clarification, and you take initiative to learn new tools and techniques independently
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You stay organized when managing multiple test setups, datasets, and deliverables, and you follow through on tasks without needing constant oversight
You will work with a cross-functional engineering team of analog and digital designers and hardware engineers with a variety of backgrounds. The R&D lab is equipped with state-of-the-art equipment for high-accuracy, high-speed test and debug, and the team takes validation seriously as a critical part of the product development cycle.
We 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.
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
