Technical-Engineering Intern
About the job
- Currently pursuing a Master's degree in Engineering, Mathematics, Physics, or Computer Science, ideally in the final years of the program.
- Familiarity with numerical methods and an interest in machine learning, optimization, and statistical techniques.
- Familiarity with C++ and Python programming, demonstrated technical skills in software development, and experience working in Windows or Linux environments.
- Ability to communicate in English, both written and verbal.
- Familiarity with surrogate modeling using tools such as Matlab, Python, C++, TensorFlow, PyTorch, Scikit-learn, or Theano.
- Understanding of computational mathematics and experience using libraries such as Python/Pandas, Python/NumPy, and Python/SciPy.
- Conduct research and development focused on optimization algorithms, metamodel techniques, and machine learning applications, combining literature review with practical software development.
- Develop and implement algorithmic prototypes using C++ and Python, creating consistent mathematical formulations and integrating them into software libraries.
- Create test cases and automated benchmarking scripts to evaluate algorithm performance on real application examples and ensure robust, reliable solutions.
- Collaborate with cross-functional teams by participating in planning meetings, gathering requirements, and presenting findings through documentation and presentations.
- Explore numerical methods, machine learning, and statistical analysis technologies while working with advanced simulation software.
About the company
Synopsys provides software tools and services for electronic design automation (EDA), helping engineers design, simulate, verify, and optimize semiconductor chips and systems. Its products cover the full design flow, including RTL-to-gating synthesis, place-and-route, timing analysis, verification, and silicon validation, as well as software integrity solutions and hardware-assisted verification. Engineers use these tools to model, simulate, and validate complex chip designs before manufacturing, reducing bugs and improving performance. Compared with many competitors, Synopsys differentiates itself through its broad, end-to-end design toolchain, large ecosystem of IP and integration with simulation and modeling capabilities gained from its 2025 merger with ANSYS, and its global scale and support. The company aims to help designers push the boundaries of chip and system performance, accelerate time-to-market, and enable silicon-to-systems design across a wide range of industries.
Company Size
10,001+
Company Stage
IPO
Headquarters
Sunnyvale, California
Founded
1986
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Simplify's Take
What believers are saying
- Synopsys raised fiscal 2027 revenue guidance to $11.15 billion on September 30, 2026.
- Management targets roughly 50% operating margin by fiscal 2030 and $1 billion buybacks.
- Ansys synergies finish early in fiscal 2027, supporting faster margin expansion.
What critics are saying
- China export restrictions slowed new projects and cut IP revenue in 2026.
- Synopsys cut 128 Sunnyvale jobs after prior 10% restructuring, signaling integration strain.
- Customers like Samsung are building in-house manufacturing tools, threatening long-term lock-in.
What makes Synopsys unique
- Synopsys and Ansys now span EDA, simulation, and silicon IP after July 2025.
- Synopsys locked AWS into a $1 billion-plus IP deal on September 30, 2026.
- GPT-Synopsys with OpenAI gives Synopsys proprietary AI workflows competitors lack.
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Benefits
- Wellness Program
- Company Equity
- Performance Bonus