AI/ML Intern

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.

Primary Responsibilities:

The AI/ML Intern will work to develop solutions to aerospace and defense problems by applying a variety of engineering, AI/ML, and software technical skills. In general, the Intern will be presented with one or more, open-ended, research problems that are related to on-going projects. This allows the Intern to directly contribute to active development and make a significant impact on the greater project success.

The Intern will utilize and develop technical skills throughout the summer as they work through their specific problems. This may include topics such as dynamical modeling and simulation, machine learning (e.g., supervised learning, reinforcement learning), statistic-based analysis, and data visualization. The aforementioned skills and solutions are expected to be implemented in software via programming languages such as Python.

To succeed in this role, the Intern will be required to leverage internal resources (e.g., software toolkits), collaborate with peers and experienced professionals, and learn independently. The Intern will also work closely with an experience mentor throughout the summer. By the end of the internship, the Intern will have the opportunity to showcase gained experience and work in company-wide events and a formal presentation.

Basic Qualifications:

• 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.

Preferred Qualifications:

• 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.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

September 11, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $48,100.00 - $86,950.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.