2027 Internship - Applied AI Engineering

Cirrus Logic • Austin, TX

1d • Hybrid

About The Position

Cirrus Logic is seeking a student intern to explore how AI and cloud-native engineering can support chip development. This R&D-facing role is intended for a master’s or PhD candidate with a strong foundation in computer science, software, or cloud engineering and an interest in working with electrical and hardware design teams.

The intern will collaborate with engineers to understand selected design and development workflows, investigate opportunities for AI, and build or evaluate a focused prototype. Work may involve Linux-based environments, scripting, cloud-native solutions, and EDA/CAD tools. The intern will receive guidance from experienced engineers and present their approach, findings, and recommendations to the team.

The role does not offer visa sponsorship. Interns follow a 2+ day in-office schedule and should expect to be in the office more often, up to five days per week, based on business needs and team preference. Interns must live within commuting distance of the listed work location or be willing to relocate before the internship begins. Candidates must be able to access technical data without Cirrus Logic obtaining an export license.

Requirements

• Be enrolled in a bachelor’s, master’s, or PhD program in computer science, computer engineering, electrical engineering, or a related field.
• Have programming or scripting experience, such as Python or shell.
• Have familiarity with Linux, version control, testing, or documentation.
• Have coursework or project experience in AI/ML, cloud, DevOps, or software systems.
• Have an interest in hardware development and cross-disciplinary collaboration.
• Demonstrate clear communication and willingness to learn from feedback.

Nice To Haves

• AI/ML research or project experience, especially involving engineering workflows.
• Exposure to cloud platforms, containers, CI/CD, or infrastructure automation.
• EDA/CAD, semiconductor, chip design, or hardware experience.
• Experience evaluating prototypes, including output quality and limitations.
• A relevant portfolio, research, publication, or class project.

Responsibilities

• Learn a chip-development workflow from a 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 work with feedback from cross-disciplinary teams.
• Document and present findings and recommendations.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern