AI Engineering Intern

About the Role

• MITRE is a nonprofit engineering, applied research, and advanced technology organization working in the public interest.
• The L576 Department combines artificial intelligence, cognitive science, and systems engineering to address complex, mission-critical decision challenges facing the U.S. government.
• The department focuses on researching, developing, and evaluating advanced AI-enabled decision support capabilities that provide timely, accurate, and actionable insights.
• Interns work alongside experienced researchers and technical professionals to explore innovative AI methods, develop and evaluate analytical models, and contribute to next-generation technologies that enhance human-AI teaming and support government sponsor decision-making.

Key Responsibilities

• Contribute to research, prototyping, and evaluation of AI-enabled decision support capabilities by reviewing literature, preparing data, implementing methods, analyzing results, and documenting findings.
• Develop and test models and software components for data pipelines, analysis, and visualization; write clean, reproducible code and use version control.
• Participate in human-AI teaming and user-centered evaluation activities; gather stakeholder feedback and translate it into improvements while following responsible AI practices.
• Collaborate with mentors and cross-functional teams; present progress and produce clear briefings and technical reports.

Requirements & Tech Stack

• Proficiency in a modern programming language (e.g., Python) and common data/ML libraries.
• Ability to write well-documented, reproducible code and use Git.
• Experience with software engineering best practices, data engineering, or MLOps.
• Comfortable with collaborative workflows and cloud environments.

Qualifications

• Current full-time BS, MS, or PhD student in Computer Science, Data Science, Electrical/Computer Engineering, Applied Mathematics, Statistics, or a related AI-focused discipline, and returning to school after the internship.
• Sustained excellence in academic performance.
• Completed or in-progress coursework in machine learning.
• Strong analytical and communication skills; able to design experiments, analyze results, and present findings to technical and non-technical audiences.
• Preferred: Experience applying AI or data-driven methods to real-world problems (course projects, research, internships, or competitions).
• Preferred: Familiarity with multiple AI approaches (e.g., machine learning, language technologies, symbolic reasoning) and integrating them in practical systems.
• Preferred: Exposure to human-centered design, evaluation, or cognitive science concepts relevant to human-AI teaming.
• Preferred: Demonstrated interest in public service and mission-focused work.
• Preferred: Contributions to research or open-source communities are a plus.