Group 24 | CO-OP | Large Language Model Researcher for Foreign Language Education | Jan
7 ore fa
The Human Health & Performance Systems Group develops human-centered technologies to overcome operational challenges and to enhance human capability in domains of interest to national security. Our research programs focus on innovative and objective solutions in the areas of integrated wearable systems, human-machine teaming, enhanced communications, neurocognitive analytics, and medical technologies. Our group is highly interdisciplinary and includes scientific experts in physiology, cognitive science, neuroscience, psychology, biomechanics, computer science, engineering, and physics. Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
Position DescriptionThe Human Health & Performance Systems Group is seeking a motivated Co-op student who is fluent in Python and enthusiastic about innovating with Large Language Models to develop tools that support foreign language learners. Our research team is an interdisciplinary group of engineers, mathematicians, linguists, and AI researchers working with multilingual datasets in areas including, but not limited to, question answering, text generation, and machine translation. In this role, you will experiment with our baseline generative AI system, conduct data analysis on multilingual corpora, design creative prompting strategies, and help define robust metrics and benchmarks to evaluate model performance in real-world foreign language education settings.
Requirements/Skills:
- Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, AI/ML, Applied Math, Computational Linguistics, or a related field
- Fluent in Python
- Strong problem-solving skills and willingness to learn new tools and methods
- Ability to work collaboratively in a team environment
Preferred (not required):
- Familiarity with Tensorflow or Pytorch
- Experience using vllm, ollama, or similar
Compensation for 2025 (will be reviewed for 2026)
- Technical Co-Op: $24.50 – $31.00 per hour (based on year in school)
- Administrative Co-Op: $21.50 – $25.00 per hour (based on year in school)
Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.
MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.
Requisition ID: 42464
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