Energy-Efficient RL Video Streaming Intern

InterDigital; Cesson-Sévigné; On-site; EUR 12,000 - 20,000; Full time

Job summary

InterDigital in France is offering an internship to explore energy-efficient adaptive video streaming using reinforcement learning. The project spans the streaming chain, from encoding and bitrate ladders to CDN delivery, with MARL considerations and QoE impact.

You will review methods, implement solutions, and benchmark against classical approaches. The role involves developing RL-based optimization, integrating device energy considerations, and potentially contributing to a scientific paper

Qualifications

• Master 2 or final year of engineering school.
• Deep learning and reinforcement learning (RL) expertise.
• Experience with adaptive streaming (HLS, DASH) and video coding.
• Programming in Python; C/C++, JavaScript.
• Knowledge of AI-assisted development tools (OpenAI Codex, Claude Code).

Responsibilities

• Conduct a state-of-the-art review of AI-based streaming approaches.
• Set up the experimental environment and document AI solutions.
• Evaluate performance and analyze results.
• Contribute to a scientific paper for international conference.

Skills

Deep learning

Reinforcement learning

Python

C/C++

JavaScript

DL frameworks

OpenAI Codex

Education

Master 2 or final year of engineering school

Tools

HLS

DASH

OpenAI Codex

Job description

InterDigital in France is offering an internship to explore energy-efficient adaptive video streaming using reinforcement learning. The project spans the streaming chain, from encoding and bitrate ladders to CDN delivery, with MARL considerations and QoE impact.

You will review methods, implement solutions, and benchmark against classical approaches. The role involves developing RL-based optimization, integrating device energy considerations, and potentially contributing to a scientific paper