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Closure Tech HW AI/ML Engineer

Closure Technologies

📍 McLean, Virginia, US0💼 Full-time🕐 5/20/2026
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Role overview

Closure Technologies is hiring for the Closure Tech HW AI/ML Engineer role in McLean, Virginia, US. It is full-time, Mid-level level, in the Tech sector. It was posted 5/20/2026.

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Role
Closure Tech HW AI/ML Engineer
Company
Closure Technologies
Location
McLean, Virginia, US
Work mode
On-site
Employment
Full-time
Seniority
Mid-level
Sector
Tech
Posted
5/20/2026

Description

• 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. Minimum Requirements • 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 Desired Skills • 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.

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