Location: Gaithersburg, MD
Cap-Exempt H-1B Position — No lottery required
**PREP Research Associate** This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research. **Research Title:** Artificial Intelligence & Machine Learning Robotics Engineer / NIST GenAI Research Associate **The work will entail:** This position involves providing software and web development support for evaluation activities in the Artificial Intelligence Group (774.02) at NIST. Specifically, the work will support NIST GenAI evaluation series ( https://ai-challenges.nist.gov/genai ). The candidate will assist in developing cutting-edge human assessment infrastructure and social cognition assessments that support evaluations in various modalities (such as text, voice, image, and video). The infrastructure includes a web platform, evaluation pipeline (backend/frontend), database schema, and other related tasks. The development includes datasets using frontier AI/LLM tools, conducting experiments, performing statistical analysis, and writing technical reports. The candidate will work alongside NIST researchers to advance measurement science through cutting-edge research and evaluations in the field of Generative AI. **U.S. Citizen Preferred** **Key responsibilities will include but are not limited to:** - Evaluating Agentic AI applications in robotics and drones within the manufacturing sector. - Analyzing AI ‑ generated content by extracting linguistic, syntactic, semantic, and structural features, and using computational methods to compare LLM judgments w