2027 Internship - Applied AI Engineering

For over four decades, Cirrus Logic has been propelled by the top engineers in mixed-signal processing. Our rockstar team thrives on solving complex challenges with innovative end-user solutions for the world's top consumer brands. Cirrus Logic is also known for its award-winning culture, which was built on a foundation of inclusion and fairness, meaningful community engagement, and delivering enjoyable employee experiences at every turn. But we couldn’t do it without our extraordinary workforce – and that’s where you come in. Join our team and help us continue to make Cirrus Logic an exceptional place to grow your career! Cirrus Logic follows a 2+ day in-office work schedule but interns should expect to be in the office more often, up to 5 days per week, based on business needs and team preference. Interns must be based within commutable distance of the work location listed on the job posting, or willing to relocate prior to beginning their internship with Cirrus Logic.   Export control restrictions based upon applicable laws and regulations would prohibit candidates who are nationals of certain embargoed countries from working in this position without Cirrus Logic first obtaining an export license.  Candidates for this role must be able to access technical data without a requirement for an export license. We are unable to sponsor or obtain export licenses for this role.   Cirrus Logic strives to select the best qualified applicant for any opening. Different approaches, ideas and points of view are both valued and respected. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, national origin, age, protected veteran or disabled status, genetic information, or any other classification protected by applicable law.

Responsibilities

Learn a chip-development workflow from your mentor and R&D partners.

Identify opportunities to apply AI to engineering tasks.

Build or evaluate a focused AI, scripting, or cloud-native prototype.

Use Linux and core software development practices.

Explore integration with EDA/CAD or engineering tools.

Refine your work with cross-disciplinary team feedback.

Document and present your findings and recommendations.

Required Skills and Qualifications

Enrolled in a bachelor's master’s or PhD program in computer science, computer engineering, electrical engineering, or related field.

Programming or scripting experience, such as Python or shell.

Familiarity with Linux, version control, testing, or documentation.

Coursework or project experience in AI/ML, cloud, DevOps, or software systems.

Interest in hardware development and cross-disciplinary collaboration.

Clear communication and willingness to learn from feedback.

Preferred Skills and Qualifications