Machine Learning for Design Verification Intern
Synopsys - Sunnyvale, California, United States, 94087
Work at Synopsys
Overview
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Overview
We Are: Drive technology innovations that shape the way we live and connect. Our technology drives the Era of Pervasive Intelligence, where smart tech and AI are seamlessly woven into daily life. From self-driving cars and health-monitoring smartwatches to renewable energy systems that efficiently distribute clean power, Synopsys creates high-performance silicon chips that help build a healthier, safer, and more sustainable world. Internship Experience:
At Synopsys, interns dive into real-world projects, gaining hands-on experience while collaborating with our passionate teams worldwide-and having fun in the process! You'll have the freedom to share your ideas, unleash your creativity, and explore your interests. This is your opportunity to bring your solutions to life and work with cutting-edge technology that shapes not only the future of innovation but also your own career path. Join us and start shaping your future today! Mission Statement:
Our mission is to fuel today's innovations and spark tomorrow's creativity. Together, we embrace a growth mindset, empower one another, and collaborate to achieve our shared goals. Every day, we live by our values of Integrity, Excellence, Leadership, and Passion, fostering an inclusive culture where everyone can thrive-both at work and beyond. What You'll Be Doing:
Developing novel machine learning techniques and large language models to improve the productivity of design verification. Contributing to ongoing research projects in the field of Design Verification. Implementing solutions using machine learning frameworks such as TensorFlow, PyTorch, Keras, and Scikit-Learn. Collaborating with cross-functional teams to integrate developed models into existing workflows. Presenting research findings and progress to stakeholders and team members. What You'll Need:
Currently enrolled in a MS/Ph.D. program in Computer Science, Electrical Engineering, or related fields with a focus on Machine Learning, Natural Language Processing, or related fields. (Advanced BS Students may also apply). Strong background in machine learning, deep learning, and transformer techniques. Good programming skills in Python, C++. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, Keras, Scikit-Learn. Familiarity with Transformers, Large language models, LangChain, LLM Alignment. Strong problem-solving skills and the ability to work independently. Good communication and teamwork skills. Familiarity with hardware description languages such as Verilog or VHDL is a plus. Experience with design verification or hardware verification is a plus. Key Program Facts:
Program Length:
12 weeks Location:
Sunnyvale, CA Working Model:
Hybrid working Full-Time/Part-Time:
Full-time Start Date:
May / June 2025 Equal Opportunity Statement:
Synopsys is committed to creating an inclusive workplace and is an equal opportunity employer. We welcome all qualified applicants to apply, regardless of age, color, family or medical leave, gender identity or expression, marital status, disability, race and ethnicity, religion, sexual orientation, or any other characteristic protected by local laws. If you need assistance or a reasonable accommodation during the application process, please reach out to us.
Inclusion and Diversity are important to us. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, military veteran status, or disability.
In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.
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