AI Security Engineer Intern

About the Role

The Software Engineering Institute (SEI) advances software engineering principles and practices, serving as a national resource in software engineering, computer security, and process improvement. AI Security Software Engineers at the SEI leverage software and machine learning engineering practices, data processing, and data analytics to address challenging AI security issues in AI Assurance, Red Teaming of AI Systems, and AI Digital Forensics, Response, and Mitigation.

This internship is within the Threat Analysis Directorate at CERT, focusing on analyzing, assuring, and countering software systems to enhance National Security. Interns will develop machine learning-based prototypes and tools to solve AI security problems and assist in the development of new technologies influencing national AI and cyber security strategy. Collaboration with AI and cyber security professionals, participation in project reviews, and presentation of work products are integral parts of this role.

Key Responsibilities

• Develop machine learning-based prototypes and tools to solve and automate solutions for AI Security problems.
• Assist in spearheading new technologies that will influence national AI and cyber security strategy.
• Collaborate with elite AI and cyber security professionals.
• Take part in project reviews to gather feedback on prototype tool approaches and solutions.
• Revise, thoroughly document, and present work products.

Job Function Breakdown

• AI Security Prototype and Tool Development: 80%
• Documentation of Results: 20%

Requirements & Tech Stack

• Enrolled in a degree-granting program.
• Must be eligible to work in the United States without Visa sponsorship.
• Able to work an internship during the summer.
• Able to work onsite at the SEI Pittsburgh office 5 days a week.
• Proficiency with a programming language, preferably Python.
• Experience with developing AI/ML solutions using common software packages and tools (e.g., PyTorch, TensorFlow).
• Basic familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis).

Qualifications

• Excellent written and verbal communication skills.
• Ability to collaborate internally and externally with professional engineers and researchers.
• Willingness to learn new technologies with cross-functional teams.
• Desired Experience:
• Basic understanding of software engineering best practices.
• Experience with adversarial machine learning techniques.
• Experience with red-teaming cyber and/or AI systems.
• Basic understanding of cybersecurity concepts.
• Experience with clearly documenting and communicating findings.