Fall 2026 Co-Op - Software Engineer (AI/ML) at cirrus

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!  In this internship, you will contribute to a focused team delivering web applications and point solutions. You’ll collaborate with cross-functional teams to support the development of scalable and reliable software tools, while gaining exposure to verification workflows and AI-enhanced methodologies.   As an intern, you’ll collaborate with experienced engineers to solve real-world challenges, contribute to product development, and gain hands-on experience in a fast-paced, supportive environment. This internship will take place during the Fall 2026 semester over the course of a 12-16 week long internship working a full-time schedule. Responsibilities • Explore and integrate AI/ML techniques to enhance productivity or automation of existing or new software applications • Collaborate with team members to support product features and verification efforts • Assist in developing and delivering AI-driven software applications and components • Contribute to both web-based and command-line tools used in design verification • Follow agile development practices and participate in team sprints • Help document and deliver software solutions Required Skills and Qualifications • Actively pursuing Masters in Computer Science or related field • Strong foundation in Python and object-oriented programming • Basic AI/ML skills including; Python libraries (NumPy, Pandas, TensorFlow, or PyTorch), Exposure to working with large language models (LLMs) and Retrieval-Augmented, Generation (RAG) techniques, Data preprocessing and analysis (cleaning, transforming, visualizing), Understanding of ML algorithms (regression, classification, clustering), Understanding of Model training and evaluation (accuracy, precision, recall, F1-score) • Familiarity with HTML, CSS, JavaScript, REST APIs • Exposure to web frameworks (e.g., Django or similar) • Basic understanding of relational databases (e.g., PostgreSQL) • Self-motivated with good communication and collaboration skills Preferred Skills and Qualifications • Prior experience with web/AI application development (personal or academic projects) • Exposure to Agile development environments • Familiarity with version control systems (e.g., Git) • Basic Linux/UNIX experience • Experience using basic AI/ML libraries 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.