Video Algorithms Intern, Video Coding (gaussian Splatting), Fall 2026

Netflix Netflix · Big Tech · Los Gatos, CA +1 · Engineering

Internship role focused on exploring and improving Gaussian Splatting (GS) for future streaming formats, involving research into model compression, training time reduction, and rendering efficiency.

What you'd actually do

  1. Explore GS model compression strategies using open datasets
  2. Contribute to early thinking on additional dataset needs for representative scenes.
  3. Characterize trade-offs among GS model size, training time, and rendered quality, and quantify the gap relative to streaming-rate targets
  4. Identify and experiment with strategies to reduce training/encoding time and/or to improve GS compression efficiency
  5. Design and implement a proof-of-concept (PoC) that showcases GS-based rendering on content of interest

Skills

Required

  • PhD in Computer Science, Engineering, Math, or Statistics
  • Strong software development skills
  • Software engineering best practices
  • Research in 3D/4D scene reconstruction, novel-view synthesis, Gaussian Splatting or NeRF, differentiable rendering, neural graphics, or 3D computer vision
  • Solid understanding of machine learning and deep learning concepts
  • Hands-on experience training and evaluating ML models
  • Python

Nice to have

  • Real-time rendering
  • GPU programming (CUDA, WebGL, graphics pipelines)
  • Video compression
  • Streaming systems
  • Codec standards (HEVC, AV1)
  • Large-scale distributed systems
  • Cloud computing

What the JD emphasized

  • expected graduation date in June 2027 or later
  • training and evaluating ML models
  • program fluently in Python

Other signals

  • Gaussian Splatting
  • 3D/4D scene reconstruction
  • novel-view synthesis
  • model compression
  • training time reduction
  • rendering quality