Remote Applied AI Intern: Build Real-World ML for Defense

Booz Allen Hamilton; Washington; On-site; USD 69,000 - 158,000; Full time

Job summary

Booz Allen Hamilton is seeking an Applied AI Intern to explore optimization, modeling, and algorithmic development within our defense mission space. You will work with data scientists, AI engineers, and mission experts to translate academic theory into mission-ready AI and machine learning solutions.

In a collaborative, Agile environment, you’ll contribute to algorithm design, model validation, experimentation, and explainability analyses, while gaining exposure to cloud environments, DevSecOps,

Qualifications

• Currently pursuing a Bachelor’s degree in Computer Science, Information Systems, or a STEM field and expected by Spring/Summer 2027.
• Experience with programming languages or frameworks (Python, Java, C++, Go, or JavaScript).
• Knowledge of software development methodologies, version control, and collaborative workflows.

Responsibilities

• Collaborate with data scientists, AI engineers, and mission experts to understand client needs and apply mathematical methods to data-driven problems.
• Evaluate performance of advanced AI/ML techniques and contribute to algorithm design, model validation, and explainability analyses.
• Develop software components and pipelines that integrate ML into operational workflows in Agile environments.

Skills

Programming languages

Office suite

Software development workflows

Secret clearance eligibility

Education

Bachelor's degree in CS/IS/STEM

Tools

Cloud platforms

Containerization

DevSecOps tooling

SQL/NoSQL databases

Job description

Booz Allen Hamilton is seeking an Applied AI Intern to explore optimization, modeling, and algorithmic development within our defense mission space. You will work with data scientists, AI engineers, and mission experts to translate academic theory into mission-ready AI and machine learning solutions.

In a collaborative, Agile environment, you’ll contribute to algorithm design, model validation, experimentation, and explainability analyses, while gaining exposure to cloud environments, DevSecOps,