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

Overview Gaussian Splatting (GS) is a 3D/4D scene reconstruction technique enabling photorealistic novel-view synthesis with low rendering complexity. As part of the Video Algorithms team during a 24‑week Fall internship, you will investigate GS as a future streaming format and explore improvements toward a practical system. Responsibilities Explore GS model compression strategies using open datasets Contribute to early thinking on additional dataset needs for representative scenes Characterize trade‑offs among GS model size, training time, and rendered quality, and quantify the gap relative to streaming‑rate targets Identify and experiment with strategies to reduce training/encoding time and/or improve GS compression efficiency Design and implement a proof‑of‑concept that showcases GS‑based rendering on content of interest Qualifications Currently pursuing a PhD in Computer Science, Engineering, Math, or Statistics with an expected graduation date in June2027 or later Thrives working in complex, dynamic, and fast‑moving environments Strong software development skills and comfortable with software engineering best practices (e.g., version control, testing, code review) Successful track record in research of 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, with hands‑on experience training and evaluating ML models Able to program fluently in Python Nice to Have Familiarity with real‑time rendering and GPU programming (CUDA, WebGL, graphics pipelines) Background in video compression, streaming systems, or codec standards such as HEVC and AV1 Involvement in open‑source multimedia or graphics projects Experience with large‑scale distributed systems and cloud computing Equal‑Opportunity Employer Statement We are an equal‑opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. At Netflix, we want to entertain the world. #J-18808-Ljbffr Netflix, Inc.