Remote Applied AI Engineer - Defense and Mission Impact

Booz Allen Hamilton

Washington (District of Columbia)

On-site

USD 69,000 - 158,000

Full time

14 days+

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Job summary

Booz Allen Hamilton is seeking an Applied AI Intern to work with our defense mission space team on optimization, modeling, probability, and algorithm development. You’ll handle large real-world data, translate theory into mission impact, and collaborate with data scientists, AI engineers, and mission experts to meet client needs.

You’ll contribute to algorithm design, model validation, and explainability analyses to ensure deployed AI is trustworthy and robust, with exposure to cloud

Qualifications

  • Experience with programming languages or frameworks such as Python, Java, C++, Go, or JavaScript.
  • Knowledge of software development methodologies, version control, and collaborative development workflows.
  • Ability to obtain a Secret clearance.
  • Scheduled to obtain a Bachelor’s degree in Computer Science, Information Systems, or a STEM field by Spring/Summer 2027.

Responsibilities

  • Collaborate with data scientists, AI engineers, and mission experts to understand client needs.
  • Apply mathematical methods to data-driven problems and evaluate AI techniques.
  • Contribute to algorithm design, model validation, analytics experiments, and explainability analysis.

Skills

Python
Java
C++
Go
JavaScript
AI/ML model development
Cloud platforms
Version control (Git)
SQL
NoSQL

Education

Bachelor's degree in Computer Science, Information Systems, or STEM field

Tools

Microsoft Office
DevSecOps tooling

Job description

Booz Allen Hamilton is seeking an Applied AI Intern to work with our defense mission space team on optimization, modeling, probability, and algorithm development. You’ll handle large real-world data, translate theory into mission impact, and collaborate with data scientists, AI engineers, and mission experts to meet client needs.

You’ll contribute to algorithm design, model validation, and explainability analyses to ensure deployed AI is trustworthy and robust, with exposure to cloud

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