AI Engineering Intern (Remote)

M3USAFort Washington, PA
Remote

About The Position

M3 USA is seeking an AI Engineering Intern to join their team. This role involves owning a project from conception to deployment, writing maintainable code, and regularly demonstrating work to various teams. The intern will collaborate with business stakeholders to understand their needs and translate them into actionable development tasks. A key aspect of the role is utilizing and evaluating AI-augmented development tools, such as agentic AI tools like Claude Code, and providing feedback on their effectiveness and limitations. The intern will also be responsible for exploring and reporting on new AI tools as they become available.

Requirements

  • Actively pursuing or recently obtained a degree in Computer Science or a related field.
  • Hands-on use of at least one AI coding agent to build something (e.g., class project, side project, hackathon entry).
  • Working knowledge of a programming language: Python, TypeScript, or similar.
  • Comfort in a terminal (e.g., not needing a GUI for git).
  • Ability to pick up unfamiliar tools by reading documentation and experimenting.

Nice To Haves

  • Web development experience (HTML, CSS, JavaScript, and any modern framework).
  • Knowledge of how Large Language Models (LLMs) work internally, beyond just prompting.
  • Experience building something that other people have used, even briefly.

Responsibilities

  • Build and ship a project end-to-end: understand the problem, build a working version, get it in front of users, and improve it based on feedback.
  • Write code that is readable and maintainable by others.
  • Demo work regularly to product, engineering, and business teams.
  • Collaborate with business stakeholders to understand their jobs and how tools can impact them.
  • Translate user needs into buildable tasks for the current week.
  • Use agentic AI tools (such as Claude Code) as a default workflow.
  • Develop judgment about where AI tools are helpful and where they produce errors.
  • Explore new AI tools as they are released and report findings, including failures, to the engineering team.
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