IAE Machine Learning Engineer Internship - Fall

• This internship supports U.S. Department of Defense-funded programs. Applicants must be U.S. citizens and eligible to obtain a security clearance. Applicants who do not meet this requirement cannot be considered for this position.
• Applicants must remain actively enrolled in an undergraduate degree program for the duration of the internship. Individuals who have already graduated prior to the internship start date are not eligible for this position.

Please Note: Authorization to work in the United States (including F-1 OPT/CPT, H-1B, or other employment authorization) does not satisfy this requirement. Applicants must be U.S. citizens to be eligible for this internship. Applicants who do not meet these eligibility requirements cannot be considered for this internship.

The University of South Florida (USF) Institute of Applied Engineering (IAE) provides agile, best-value engineering solutions to enhance the performance, effectiveness of its sponsors, including the Department of Defense; other federal, state, and local agencies; and industry. These engineering solutions include hardware-and-software-based research, advanced technology development, prototypes, and technical services.

The position title for this job application is “Machine Learning Engineer Intern”. This internship program will complement CDAO, J8, and its component persistent workforce, enabling them to develop solutions to data-related problems. The Intern will work with the CDAO and J8 Team to develop business analytic methodologies and tools to support Special Operations resourcing decisions.

• Hours of operation are 8:00am to 5:00pm Monday thru Friday.
• This position requires 20 hours per week during the Fall/Spring semesters and 29 hours per week during the Summer semester.
• Estimate
  
  Start Date:
  
  11-2026 or 01-2027. End-date: 05-2027 (possible extension to 12-2027)
• This internship is in-person (Tampa, FL) with limited remote work opportunities. Located at Mac Dill Air Force Base

• Build resume and explore career options
• Apply skills and knowledge to the workplace
• Upon completion of the internship, a letter of recommendation can be provided upon request
• Opportunity for extension of internship into 2027.

$18.50/hour

• Build and maintain data pipelines within Palantir’s Maven Smart Systems (MSS) to ensure mission datasets are properly ingested, validated, structured, and optimized for analytic and machine‑learning workflows.
• Design and implement AI/ML workflows inside MSS, including feature engineering, model evaluation, and preparing model outputs for operational use across CDAO and J8.
• Develop MSS‑based analytic tools that support SOF resourcing analysis, enabling data‑driven tradeoffs, trend identification, and visualization of operational insights.
• Create user‑facing applications and interfaces in MSS that allow analysts and decision‑makers to interact with models, dashboards, and mission datasets without technical barriers.
• Prototype, test, and document machine‑learning models that address SOCOM problem sets, collaborating with engineers to transition prototypes into stable, platform‑ready components.
• Integrate ML and analytic components into MSS ontologies and operational workflows, ensuring alignment with SOCOM data structures, access controls, and deployment practices.
• Work directly with mission analysts to refine requirements, translating operational questions into technical tasks and ensuring outputs meet decision‑maker needs.
• Support data governance and accountability through documentation, version control, and adherence to SOCOM data‑handling standards.
• Participate in sprint reviews, design sessions, and technical exchanges to support rapid…