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Intern Llm Developer Jobs in Virginia (NOW HIRING)

Interon IT Solutions

GenAI Intern

Chantilly, VA · On-site

Job Title- Generative AI Engineer / GenAI Intern Product Development | Interon IT Solutions ... Build LLM-powered applications using platforms such as OpenAI, Azure OpenAI, AWS Bedrock, Anthropic ...

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Intern Llm Developer information

What does an intern LLM developer do?

An Intern LLM (Large Language Model) Developer supports the development, testing, and deployment of AI models, specifically large language models like GPT or BERT. Their responsibilities often include data preprocessing, model fine-tuning, writing code to interact with APIs, and evaluating model performance. Interns work under the guidance of senior developers and researchers to gain hands-on experience in natural language processing and AI. This role is ideal for students or recent graduates looking to build practical skills in machine learning and AI development.

What are the key skills and qualifications needed to thrive as an intern LLM developer?

To thrive as an Intern LLM Developer, you generally need a solid background in computer science, programming (especially Python), and foundational knowledge of machine learning concepts. Familiarity with deep learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and exposure to large language models (LLMs) are typically required. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate and learn in dynamic team environments. These skills and qualities are vital for contributing to cutting-edge AI projects and rapidly adapting to evolving technologies in the field.

What types of projects and learning opportunities can an intern LLM developer expect during their internship?

As an Intern LLM Developer, you can expect to participate in hands-on projects involving the development, fine-tuning, or evaluation of large language models (LLMs). Typical responsibilities include data preprocessing, implementing model training pipelines, and collaborating with senior engineers and data scientists to optimize model performance. You'll also have opportunities to contribute to research on natural language processing (NLP) tasks and gain exposure to industry-standard tools and frameworks. This role offers valuable mentorship and the chance to build practical skills in machine learning and AI, setting a strong foundation for a future career in the field.

What is the difference between Intern Llm Developer vs Intern Machine Learning Engineer?

AspectIntern Llm DeveloperIntern Machine Learning Engineer
Required CredentialsTypically pursuing or recent graduate in Computer Science, AI, or related fieldsSimilar educational background, often with focus on ML or AI
Work EnvironmentTech companies, AI startups, research labsTech firms, startups, research institutions
Employer & Industry UsageFocused on developing large language models and NLP applicationsDeveloping various ML models, including NLP, computer vision, etc.
Common Search & ComparisonIntern Llm Developer vs Intern Machine Learning Engineer

Intern Llm Developers primarily focus on building and fine-tuning large language models, often specializing in NLP tasks. Intern Machine Learning Engineers have a broader scope, working on various ML models across different domains. Both roles require similar educational backgrounds and are found in tech and AI industries, but their specific focus areas differ.

What are the most commonly searched types of Llm Developer jobs in Virginia?

The most popular types of Llm Developer jobs in Virginia are:

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For Intern Llm Developer jobs in Virginia, the most frequently searched job titles are:

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Intern Llm Developer jobs near you

GenAI Intern

Chantilly, VA • On-site

Interon IT Solutions
See more jobs at Interon IT Solutionsexternal

Full-time

Posted 6 days ago

Job description

Job Title- Generative AI Engineer / GenAI Intern

Product Development | Interon IT Solutions

Location: Chantilly, Virginia — Onsite

Experience: 1–5 years; internship and entry-level candidates considered

Employment: Full-time / Internship

Work Authorization: U.S. Citizen or Green Card holder

Department: Product Development / AI Engineering

About the Role

Interon IT Solutions is seeking a hands-on Generative AI Engineer or GenAI Intern to help build AI-powered enterprise and healthcare products. You will work with product and engineering teams to take practical AI use cases from concept and prototyping through development, testing, deployment, and continuous improvement.

The ideal candidate enjoys building real applications with LLMs, Retrieval-Augmented Generation (RAG), AI agents, APIs, and cloud technologies—not simply experimenting with prompts or AI tools.

Key Responsibilities
  • Design, develop, test, and enhance Generative AI features for Interon products.
  • Build LLM-powered applications using platforms such as OpenAI, Azure OpenAI, AWS Bedrock, Anthropic, or similar services.
  • Develop RAG solutions using enterprise documents and structured or unstructured data.
  • Build AI agents and agentic workflows with tool calling, context management, and multi-step automation.
  • Implement prompt engineering, structured outputs, grounding, guardrails, and response-quality controls.
  • Design retrieval systems using embeddings, vector search, semantic search, and hybrid search.
  • Develop backend APIs and microservices with Python, FastAPI, Node.js, or comparable frameworks.
  • Integrate AI capabilities with enterprise applications, databases, APIs, and business workflows.
  • Support AI-powered web applications using React, TypeScript, or modern frontend frameworks.
  • Evaluate LLM applications for accuracy, relevance, hallucinations, latency, security, and cost.
  • Implement testing, logging, monitoring, observability, and evaluation processes for GenAI applications.
  • Deploy and operate AI applications using AWS and/or Azure services.
  • Participate in Git-based development, code reviews, CI/CD, technical documentation, and collaboration with product owners and business teams.
  • Research emerging GenAI technologies and recommend practical applications for Interon products.
Required Qualifications
  • 1–5 years of experience in software development, AI/ML, data engineering, or a related technical field. For internship or entry-level candidates, academic projects, internships, hackathons, or independently developed applications may substitute for professional experience.
  • Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or a related field.
  • Strong Python programming skills and working knowledge of REST APIs, JSON, databases, and backend development.
  • Understanding of Generative AI, LLMs, embeddings, prompt engineering, RAG, and AI application design.
  • Experience or project exposure with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.
  • Familiarity with SQL, relational databases, Git/GitHub, and modern software development practices.
  • Strong analytical, problem-solving, communication, and collaboration skills.
  • Ability to learn new AI technologies quickly and work onsite in Chantilly, Virginia.
  • Must be a U.S. Citizen or U.S. Permanent Resident (Green Card holder).
Preferred Qualifications
  • Azure AI Foundry or Azure OpenAI
  • AWS Bedrock or OpenAI APIs
  • Agentic AI, LangGraph, or multi-agent workflows
  • RAG architecture, vector databases, PostgreSQL/pgvector, or Azure AI Search
  • React, TypeScript, or FastAPI
  • AWS Lambda, API Gateway, S3, RDS, or related cloud services
  • Docker, GitHub Actions, CI/CD, AI evaluation, or observability
  • Healthcare technology, HR technology, workflow automation, or enterprise SaaS
Potential Product Initiatives

The selected candidate may contribute to production-oriented solutions such as:

  • AI-powered HR and recruiting solutions
  • Candidate and resume matching
  • Enterprise knowledge assistants and RAG applications
  • AI agents for business workflow automation
  • Healthcare workflow and administrative automation
  • Document intelligence and information extraction
  • Prior authorization and payer knowledge solutions
  • AI-powered analytics and decision-support capabilities
What We Value

We value candidates who can demonstrate what they have built. A GitHub portfolio, working prototype, hackathon project, or independently developed application involving RAG, AI agents, LLM integrations, semantic search, workflow automation, API development, or cloud-based AI will be a strong advantage.