Applied AI & Math Intern — Defense Tech Impact

Booz Allen Hamilton; McLean (VA); On-site; USD 55,000 - 126,000; Full time

Benefits offered by this job

Health insurance

Life insurance

Disability benefits

Retirement benefits

Paid leave

Professional development

Tuition assistance

Work-life programs

Dependent care

Job summary

Booz Allen Hamilton is seeking a University Applied AI Software Development Intern in McLean, VA. You will collaborate with data scientists, AI engineers, and mission experts to apply mathematical methods to data-driven challenges and to evaluate the performance of AI and ML techniques.

You will support algorithm design, model validation, analytic experimentation, and explainability work to ensure deployed AI is trustworthy, robust, and operationally effective.

Qualifications

• Pursuing a Bachelor’s degree in CS, Engineering, Information Systems, or a STEM field by Spring or Summer 2028.
• Experience with programming languages or frameworks including Python, Java, C++, Go, or JavaScript.
• Knowledge of software development methodologies, version control, and collaborative development workflows.
• Willingness to travel up to 25% of the time and to obtain a Secret clearance.

Responsibilities

• Assist in algorithm design, model validation, and analytic experimentation.
• Explainability analysis to ensure trusted AI performance.
• Collaborate with data scientists, AI engineers, and mission experts to apply mathematical methods to data-driven challenges.

Skills

Python

Java

C++

Go

JavaScript

Education

Bachelor’s degree in CS/Engineering/IS/STEM

Tools

Git

Cloud platforms

DevSecOps tooling

Job description

Booz Allen Hamilton is seeking a University Applied AI Software Development Intern in McLean, VA. You will collaborate with data scientists, AI engineers, and mission experts to apply mathematical methods to data-driven challenges and to evaluate the performance of AI and ML techniques.

You will support algorithm design, model validation, analytic experimentation, and explainability work to ensure deployed AI is trustworthy, robust, and operationally effective.