AI Video Engineer Intern

E1; United States; Remote; USD 25,000 - 39,000; Part time

Job summary

E1 is seeking an AI Video Engineer Intern to help build systems for processing and verifying video content, blending video pipelines with computer vision or multimodal ML. You will experiment and evaluate while turning successful prototypes into robust production software and documenting limitations clearly.

The role emphasizes turning experiments into production-ready code and collaborating across data preparation, experimentation, and engineering to support the verification workflow with

Qualifications

• Pursuing CS/ML degree or equivalent study
• Proficiency in Python and ML workflows
• Experience with computer vision or multimodal ML
• Familiarity with video processing concepts
• Strong experimental discipline and clear comparisons
• Interest in translating prototypes to production code

Responsibilities

• Develop pipelines to ingest, transform, and analyze video assets
• Apply vision or multimodal models to real footage and assess performance
• Design evaluations to track model quality and ensure reproducible results
• Record failure modes and known limitations for model improvement
• Prototype approaches and harden promising methods into production code
• Collaborate across data prep, experimentation, and engineering for verification workflows

Skills

Python

ML workflows

Computer vision

Multimodal ML

Video processing

Experimentation

Education

Pursuing CS/ML degree

Tools

TensorFlow

PyTorch

Job description

Role overview

As an AI Video Engineer Intern, you will help build the systems used to process and verify video content. Your work will combine video pipelines with computer vision or multimodal machine-learning models, supporting reliable analysis of creator footage. The role includes experimentation and evaluation, but also requires turning successful prototypes into robust production software and documenting limitations clearly.

Responsibilities

• Develop pipelines that ingest, transform, and analyze video assets at different stages of processing.
• Apply vision or multimodal models to real-world footage and assess how well they perform.
• Design meaningful evaluations, track model quality, and distinguish repeatable results from fortunate examples.
• Record failure modes, edge cases, and known limitations so that model behavior can be understood and improved.
• Prototype approaches quickly, then harden promising methods into maintainable production code.
• Work across data preparation, experimentation, and engineering implementation as needed by the verification workflow.

Requirements

• Studying computer science or machine learning, or building equivalent capability through self-directed learning, coursework, or personal projects.
• Proficiency in Python.
• Familiarity with common machine-learning tools and workflows.
• Academic or project experience involving computer vision, multimodal machine learning, or video processing.
• Sound experimental discipline, including the ability to form clear comparisons and avoid overclaiming from limited evidence.
• Comfort investigating why a model succeeds or fails rather than focusing only on headline metrics.

This internship suits someone who enjoys combining applied machine learning with practical software engineering and who treats evaluation quality, reproducibility, and transparent reporting as essential parts of the work.