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About Netflix
Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media
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As part of the Video Algorithms team at Netflix, this 24-week Fall internship focuses on advancing Gaussian Splatting (GS) for photorealistic novel-view synthesis, aiming to reduce model training time and improve compression efficiency. Interns will explore GS model compression strategies using open datasets, contribute to dataset needs, characterize trade-offs between model size, training time, and rendered quality, and experiment with methods to enhance GS performance. Additionally, they will design a proof-of-concept for GS-based rendering on relevant content. Ideal candidates are PhD students in technical fields like Computer Science or Engineering, with expertise in 3D/4D scene reconstruction, novel-view synthesis, and Gaussian Splatting. Strong software development skills in Python, along with experience in machine learning and deep learning, are essential. Familiarity with real-time rendering, GPU programming, video compression standards, and large-scale distributed systems is a plus.
Explore GS model compression strategies using open datasets.
Characterize trade-offs among GS model size, training time, and rendered quality.
Identify and experiment with strategies to reduce training/encoding time for GS.
Design and implement a proof-of-concept showcasing GS-based rendering on content of interest.
Contribute to early thinking on additional dataset needs for representative scenes.
What we're looking for
Currently pursuing a PhD expected to graduate June 2027 or later.
Strong experience in research of 3D/4D scene reconstruction, novel-view synthesis, Gaussian Splatting, NeRF, differentiable rendering, neural graphics, or 3D computer vision.
Solid understanding and hands-on experience with machine learning and deep learning concepts.
Fluent programming skills in Python.
Proficient software development skills including version control, testing, code review practices.
Thrives in complex, dynamic, fast-moving environments.
PyTorch
TensorFlow
CUDA
Python
Deep Learning
Computer Vision
Machine Learning
Generative Modeling
Optical Flow
Perceptual Quality
ML for Video Compression
CI/CD