AI Engineering Intern
About The Position
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 researches, develops, and evaluates 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. The intern contributes to research, prototyping, and evaluation of AI-enabled decision support capabilities, including reviewing literature, preparing data, implementing methods, analyzing results, and documenting findings. The role also involves developing and testing models and software components for data pipelines, analysis, and visualization, as well as participating in human-AI teaming and user-centered evaluation activities.
Requirements
- Be a 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 return to school after the internship.
- Demonstrate sustained excellence in academic performance and completed or in-progress coursework in machine learning.
- Be proficient in a modern programming language (e.g., Python) and common data/ML libraries; be able to write well-documented, reproducible code and use Git.
- Have strong analytical and communication skills, including the ability to design experiments, analyze results, and present findings to technical and non-technical audiences.
Nice To Haves
- Experience applying AI or data-driven methods to real-world problems through course projects, research, internships, or competitions.
- Familiarity with multiple AI approaches, such as machine learning, language technologies, or symbolic reasoning, and integrating them in practical systems.
- Exposure to human-centered design, evaluation, or cognitive science concepts relevant to human-AI teaming.
- Experience with software engineering best practices, data engineering, or MLOps; comfort with collaborative workflows and cloud environments.
- Demonstrated interest in public service and mission-focused work; contributions to research or open-source communities are a plus.
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.
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
