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Internship Retrieval Augmented Generation Jobs in Virginia

Closure Technologies

AI/ML Engineer

Mclean, VA

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 ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Job Summary : Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into ...

Closure Technologies

AI/ML Engineer

Mclean, VA · On-site

Job Summary : Closure Technologies is seeking an AI/ML Engineer who will implement and maintain Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs) into ...

System One Holdings, LLC

AI/ML Engineer

Mclean, VA · On-site

This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows, traditional machine learning, natural language processing, graph analytics, and entity resolution.

System One

AI/ML Engineer

Mclean, VA · On-site

This position will focus on Retrieval-Augmented Generation, conversational AI, agentic workflows, traditional machine learning, natural language processing, graph analytics, and entity resolution.

Accenture Federal Services

AI Engineer

Arlington, VA · On-site

Architect and deploy Retrieval-Augmented Generation (RAG) solutions and AI orchestration frameworks * Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible ...

Accenture Federal Services

AI Engineer

Arlington, VA · On-site

Architect and deploy Retrieval-Augmented Generation (RAG) solutions and AI orchestration frameworks * Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible ...

ECS

Sr. Data Scientist

Fairfax, VA · On-site

$175K - $205K/yr

In this role, you will design and optimize next-generation search and retrieval experiences using Elasticsearch, Vector Search, and Retrieval-Augmented Generation (RAG) techniques to improve ...

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Internship Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as an intern working with Retrieval Augmented Generation (RAG), and why are they important?

To thrive as an intern in Retrieval Augmented Generation, you need a foundational understanding of natural language processing, machine learning concepts, and strong programming skills, often supported by coursework or research in computer science or data science. Familiarity with tools like Python, PyTorch or TensorFlow, and experience with libraries such as Hugging Face Transformers and vector databases are typically required. Strong analytical thinking, curiosity, and effective communication make candidates stand out in collaborative, research-intensive environments. These abilities are critical for developing, evaluating, and improving RAG systems that combine information retrieval with generative models.

What is an Internship in Retrieval Augmented Generation (RAG)?

An Internship in Retrieval Augmented Generation (RAG) is a temporary position, typically for students or early-career professionals, focused on developing or researching AI systems that combine information retrieval with generative models. Interns in this field may work on enhancing how AI models find and use external data sources to generate accurate, context-aware responses. This role often involves tasks such as data preprocessing, implementing retrieval algorithms, fine-tuning language models, and evaluating system performance. It offers valuable hands-on experience with cutting-edge AI technologies and frameworks.

What types of projects or tasks can I expect to work on during an Internship in Retrieval Augmented Generation (RAG)?

As an intern in Retrieval Augmented Generation, you can expect to work on projects that involve integrating information retrieval systems with generative AI models. Typical tasks may include curating and preprocessing data sets, developing or fine-tuning retrieval algorithms, evaluating the performance of RAG pipelines, and collaborating with engineers and researchers to improve end-to-end system accuracy. You may also assist in conducting experiments, analyzing results, and documenting findings, all within a collaborative team environment that values innovation and knowledge sharing.

What is the difference between Internship Retrieval Augmented Generation vs Internship Data Analyst?

AspectInternship Retrieval Augmented GenerationInternship Data Analyst
Required SkillsKnowledge of AI, NLP, retrieval systems, programmingData analysis, statistical skills, Excel, SQL
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing departments
Employer UsageDevelop AI models, improve retrieval systemsAnalyze data trends, generate reports

Internship Retrieval Augmented Generation focuses on developing AI models that combine retrieval systems with language generation, requiring skills in AI and programming. In contrast, an Internship Data Analyst concentrates on analyzing data sets to inform business decisions, emphasizing statistical and analytical skills. Both roles are common in tech and business sectors but serve different functions within organizations.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Virginia? The most popular types of Retrieval Augmented Generation jobs in Virginia are:
What are popular job titles related to Internship Retrieval Augmented Generation jobs in Virginia? For Internship Retrieval Augmented Generation jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Internship Retrieval Augmented Generation jobs in Virginia look for? The top searched job categories for Internship Retrieval Augmented Generation jobs in Virginia are:
What cities in Virginia are hiring for Internship Retrieval Augmented Generation jobs? Cities in Virginia with the most Internship Retrieval Augmented Generation job openings:
Internship Retrieval Augmented Generation jobs near you
Infographic showing various Internship Retrieval Augmented Generation job openings in Virginia as of June 2026, with employment types broken down into 7% Internship, 68% Full Time, 7% Part Time, and 18% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution.

AI/ML Engineer

Closure Technologies

Mclean, VA

Full-time

Posted 7 days ago

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.