University - Applied AI Intern

Booz Allen Hamilton
Remote / Hybrid / Onsite2026-03-27Part time

About the job

Artificial Intelligence is only as strong as the mathematical foundations behind it. As an Applied AI Intern, you’ll help our defense mission space team explore new approaches in optimization, modeling, probability, and algorithmic development to advance next-generation mission solutions. You’ll work with massive real-world data sets and operationally relevant challenges, giving you the opportunity to translate academic theory into meaningful national security impact.

Responsibilities

Collaborate closely with data scientists, AI engineers, and mission experts to understand client needs, apply mathematical methods to data-driven problems, and evaluate the performance of advanced AI and machine learning techniques. Contribute to algorithm design, model validation, analytic experimentation, and explainability analysis to help ensure deployed AI is trustworthy, robust, and mission-ready. Build tools, applications, and pipelines that integrate machine learning into real world operational workflows and advanced analytical systems. Collaborate with multidisciplinary teams to explore emerging AI technologies, evaluate integration approaches, and develop software components that enhance mission-relevant decision making. Work in Agile environments where you can rapidly iterate, test new features, incorporate user feedback, and gain exposure to cloud environments, DevSecOps toolchains, and secure development best practices.

Qualifications

Minimum

Experience with programming languages or frameworks, including Python, Java, C++, Go, or JavaScript

Experience with Microsoft Office, including Outlook, Word, Excel, and PowerPoint

Knowledge of software development methodologies, version control, and collaborative development workflows

Ability to obtain a Secret security clearance

Scheduled to obtain a Bachelor’s degree in Computer Science, Information Systems, or a STEM field by Spring/Summer 2027

Preferred

Experience with AI and ML model development or integration

Experience with cloud platforms, containerization, or DevSecOps tooling

Experience with databases such as SQL or NoSQL or data engineering pipelines

Knowledge of Agile development