AI/LLM Engineering Internship

Category Interns/Temp Hire Type Intern Job ID 15055 Base Salary Range $0-$0 Remote Eligible No Date Posted 04.08.2026

Introduction:

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:

• Assist in developing AI/LLM features to address engineering challenges and enable natural language interaction with the Ansys Mechanical application.
• Enhance coding agent workflows by providing instructions and skills to help developers work faster and more efficiently.
• Collaborate with a network of expert professionals to achieve development objectives and share innovative ideas.
• Investigate and resolve defects in production code, ensuring high-quality software delivery.
• Develop unit tests for new features and analyze results to improve software usability.

What You’ll Need:

• Currently pursuing a degree in Computer Science, Artificial Intelligence, Mechanical, Aerospace, or a related engineering field.
• Experience with Large Language Models (LLM).
• Familiarity with coding agents such as GitHub Copilot for development purposes.
• Proficiency in scripting languages such as Python.
• Excellent analytical and algorithmic thinking skills.
• Strong written and oral communication abilities.

Preferred Qualifications and Skills:

• Experience with Microsoft Visual Studio and software configuration management tools (SVN, GIT) and GitHub.
• Background in Machine Learning, including LLM concepts like Retrieval Augmented Generation (RAG), Natural Language Processing, and graph algorithms.
• Good knowledge of at least one of the following programming languages: C++, C#, Go, Rust, or Java.

Key Program Facts:

• Program Length: 3 months
• Location: Canonsburg, PA
• Working Model: In-office
• Full-Time/Part-Time: Full-time
• Start Date: May 2026

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.

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.

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 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.