AI/ML Intern

Leidos•Huntsville, AL

1d•Onsite

About The Position

Leidos is seeking a talented AI/LM Intern for Summer 2027. In the Leidos Autonomy and Artificial Intelligence branch, you will work to solve complex engineering problems with a highly technical, multidisciplinary team consisting of aerospace engineers, computer scientists, research scientists, and statisticians. This group provides cutting-edge solutions to aerospace and defense problems such as autonomous battle management, robotic vehicle guidance, and model-based system identification.

Requirements

Working towards a bachelor's degree in Aerospace Engineering, Computer Science, Mathematics, or a related field from an accredited college or university.
Advanced proficiency in programming, specifically including Python and MATLAB.
Fundamental understanding of mathematical concepts, including linear algebra, matrix math, statistics, trigonometry, and coordinate frames.
Fundamental understanding of core aerospace concepts, such as vehicle and attitude dynamics, control systems, and flight mechanics.
Understanding of machine learning basics, supervised learning, reinforcement learning, and statistics.
Effective technical communication skills.
Ability to perform independent research to learn new skills.
Ability to work both in collaborative team environments and independently on open-ended research problems.
Ability to relocate to work on-site at the Huntsville, AL office.
Ability to obtain and maintain a TS/SCI with CI Poly Security Clearance.

Nice To Haves

Working towards a graduate degree from an accredited college or university.
Experience with research.
Experience with C++.
Experience with Linux.
Experience with version control systems (e.g. Git).
Obtained an active Security Clearance.

Responsibilities

Develop solutions to aerospace and defense problems by applying a variety of engineering, AI/ML, and software technical skills.
Work on one or more open-ended, research problems related to on-going projects.
Directly contribute to active development and make a significant impact on project success.
Utilize and develop technical skills in dynamical modeling and simulation, machine learning (e.g., supervised learning, reinforcement learning), statistic-based analysis, and data visualization.
Implement skills and solutions in software via programming languages such as Python.
Leverage internal resources (e.g., software toolkits).
Collaborate with peers and experienced professionals.
Learn independently.
Work closely with an experienced mentor.
Showcase gained experience and work in company-wide events and a formal presentation.