AI/ML Engineer, McLean

Job Description

Job Description Closure Technologies

is seeking a

AI/ML Engineer

who will Implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into applications, supported by API development and optimizing data storage through Postgres schema refinement. Clearance Requirement:

TS/SCI with Polygraph Key Responsibilities: Implement and maintain RAG pipelines, including document processing, embedding generation, retrieval configuration, and prompt assembly. Integrate LLMs into applications using available APIs and frameworks. Develop and maintain REST API interactions to support data retrieval and system integration.Design or refine Postgres schemas to improve data organization and query performance. Required Qualifications: Demonstrated ability to conduct independent technical research, evaluate emerging AI/ML approaches, and apply advanced analytical problem-solving comparable to PhD-level research environments.Ability to rapidly learn and apply new AI/ML methodologies, tools, and frameworks in support of evolving mission requirements. Experience developing AI/ML applications focused on Retrieval-Augmented Generation (RAG), semantic retrieval, LLM integration, or related AI workflows. Strong proficiency in Python and modern AI/ML libraries, frameworks, and API integrations.Active/current TS/SCI with required polygraph. Willingness to work onsite full time. US citizenship required. Senior Labor Category: Minimum 8 years of experience with a Bachelor's degree; or 7 years of experience with a Masters degree; or 6 years of experience with a Doctorate Preferred Qualifications:Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. Experience publishing research, contributing to open-source AI/ML initiatives, or leading experimental and prototype development efforts.Familiarity with model evaluation frameworks, fine-tuning workflows, inference optimization, and AI

observability/monitoring

tools. Experience with vector databases, AWS/cloud environments, Docker, and containerized AI/ML development workflows. Experience designing and integrating REST APIs and scalable data architectures.