Machine Learning / AI Engineering Internship (LLM Focus)

Aone Consulting, LLC; United States; Remote; USD 11,160; Full time

Job summary

A tech consulting firm in the United States is seeking a Machine Learning / AI Engineering Intern focused on LLM. This paid internship lasts 8 weeks and offers a stipend of $1,000 per month. Interns will work on enhancing an LLM+VLM tool for analyzing data from various sources, participating in backend development and API design. Candidates should have a solid understanding of distributed systems, Docker, Python, and API usage. This role provides hands-on experience in a professional tech environment.

Qualifications

• Strong understanding of distributed and concurrent systems expected.
• Proficiency in Docker, Python, and REST is essential.
• Must understand LLM/VLM API usage and on-premises infrastructure.

Responsibilities

• Play a pivotal role in software stack development and AI integration.
• Continue the development of an LLM+VLM tool for data analysis.
• Ensure secure connections to external systems for document ingestion.

Skills

Distributed systems

Concurrent systems

Docker

Python

REST

LLM/VLM API usage

On-premises infrastructure

Education

Currently enrolled in an accredited college or university pursuing a degree in Computer Science or related field

Job description

Machine Learning / AI Engineering Internship (LLM Focus)

During this internship, you will play a pivotal role in accelerating a fast-moving project encompassing software stack development, Artificial Intelligence, Computer Vision, and network interoperability.

Duration- 8 weeks (June- early August)

This internship project focuses on continuing the development of an LLM+VLM tool that supports both multi modal content and external enterprise data sources.

The objective is to give users a unified way to ask questions, analyze documents, and build retrieval workflows, whether the data comes from local files, images, scanned documents, and external sources.

The intern(s) will join an existing team to continue the framework that allows the platform to securely connect to external systems.

This includes support for authentication, configuration, connection health checks, source discovery, and document ingestion into existing analysis and RAG pipelines.

The project will emphasize clean architecture so new connectors can be added later with minimal changes to the core platform.

Attention will be given to multi-user and multi-organization requirements such as role-based access control, token-based access, and separation of data between organizations and users.

Because some tasks may take time to complete, the internship will integrate a job management model for long-running operations such as batch analysis, ingestion, and indexing. This includes thinking about queue visibility, task status, and scalable execution in a multi-user environment.

This project is well-suited for a student interested in AI systems, backend development, API design, multi modal AI, and secure enterprise integration.

A strong understanding of distributed and concurrent systems, Docker, Python, REST, LLM/VLM API usage, and on-premises infrastructure is expected of candidates.

By the end of the internship, the students will present the features and abilities added to corporate leaders.

Requirements

A strong understanding of distributed and concurrent systems, Docker, Python, REST, LLM/VLM API usage, and on-premises infrastructure is expected of candidates.

Must be currently enrolled in an accredited college or university pursuing a degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field

Fields/ Disciplines Used:

• Artificial intelligence (AI) fundamentals
  
• Retrieval-augmented generation (RAG)
  
• Backend software engineering
  
• API design and integration
  
• Distributed and concurrent systems
  
• Enterprise systems integration
  
• Identity and access management (RBAC)
  
• Cloud and on-prem infrastructure
  

This internship offers a stipend of $1,000 per month. This is a paid internship opportunity and does not include additional compensation or benefits such as health insurance, retirement plans, or paid time off. The internship is designed to provide hands-on experience, skill development, and exposure to real-world projects in a professional environment.