AI/ML Video Solutions Intern

DIRECTV; Detroit (MI); On-site; USD 34,000 - 47,000; Part time

Job summary

DIRECTV is offering a Summer Intern position in business AI/ML. The role is an in-person 10-week internship based in Clarksburg, MD, focusing on AI/ML for media solutions and customer experience.

You’ll work with Python and ML tools within the Product Development organization on real-world problems. The program emphasizes model development, data processing, and evaluation, with hands-on projects across CNNs, transformers, and NLP, in a collaborative environment.

Qualifications

• Proficiency in Python and its ML ecosystem (NumPy and pandas).
• Ability to write reproducible training and evaluation scripts.
• Assist in selecting ML approaches based on data and problem type.
• Support end-to-end model development lifecycle from data to validation.
• Build and benchmark baseline models (linear regression, decision trees, SVM).
• OS and tools: Linux and OpenAI API, Claude Code.

Responsibilities

• Develop AI/ML tools and contribute to an AI-powered media platform.
• Work with video metadata, captions, transcripts, and AI/ML models.
• Evaluate models, preprocess data, and build prototype tools/dashboards.
• Collaborate across teams and present findings effectively.
• Prototype DL architectures (CNNs, RNNs, transformers) using PyTorch/TF.

Skills

Python

ML ecosystem (NumPy, pandas)

Write training/evaluation scripts

Data preprocessing/feature extraction

Model selection (supervised, unsupered

Education

Undergrad in AI/CS/Software Engineering/Info Tech/Data Science

Tools

Linux

OpenAI API

Claude Code

PyTorch

TensorFlow

Android

Job description

DIRECTV is offering a Summer Intern position in business AI/ML. The role is an in-person 10-week internship based in Clarksburg, MD, focusing on AI/ML for media solutions and customer experience.

You’ll work with Python and ML tools within the Product Development organization on real-world problems. The program emphasizes model development, data processing, and evaluation, with hands-on projects across CNNs, transformers, and NLP, in a collaborative environment.