Netflix Video Algorithms Intern Fall 2026 | Gaussian Splatting
Rolling applications — apply early
| Company | Netflix — Engineering / Streaming · Video Algorithms |
| Role | Video Algorithms Intern, Video Coding (Gaussian Splatting), Fall 2026 · JR40251 |
| Location | Los Gatos, CA (team may also place in Los Angeles, CA) |
| Duration | 24-week Fall 2026 internship (Netflix internships are typically ≥12 weeks) |
| Pay | Intern market range typically $40–$110/hour (total compensation; varies by role/location) |
| Eligibility | Currently pursuing a PhD in CS, Engineering, Math, or Statistics; expected graduation June 2027 or later |
| Focus | Gaussian Splatting compression · novel-view synthesis · streaming-format research · Python / ML |
Overview
Gaussian Splatting (GS) enables photorealistic novel-view synthesis with low rendering complexity — attractive for TVs, streaming sticks, phones, and laptops. The open challenges: much faster model training/encoding and more efficient compression.
On the Video Algorithms team during this 24-week Fall internship, you’ll investigate GS as a future streaming format and build toward a practical system: compression strategies on open datasets, size/training-time/quality trade-offs vs streaming-rate targets, experiments to cut encoding time or improve compression, and a proof-of-concept GS rendering pipeline on content of interest.
Key Requirements
- Eligibility: PhD student in CS, Engineering, Math, or Statistics with expected graduation June 2027 or later.
- Research fit: Track record in 3D/4D scene reconstruction, novel-view synthesis, Gaussian Splatting or NeRF, differentiable rendering, neural graphics, or 3D computer vision.
- Skills: Strong software engineering practices (VCS, testing, code review); solid ML/DL fundamentals with hands-on model training/eval; fluent Python.
- Nice to have: Real-time rendering / GPU (CUDA, WebGL); video compression or codecs (HEVC, AV1); open-source multimedia/graphics; large-scale distributed systems / cloud.
- Why it stands out: Long 24-week research internship on next-gen streaming; embed with Netflix Video Algorithms; publish-adjacent work on GS for consumer devices.
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