Drimva

TikTok

Research Engineer - Intern (Video and Edge, Multimedia Lab) - 2027 Start (PhD) - Intern (Video and Edge, Multimedia Lab) - 2027 Start (PhD)

San Diego, California · Internship · Posted Oct 28, 2026

Education
Currently pursuing a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related technical field.

About the job

Research and prototype machine-learning-based video coding and processing methods, optimizing codec systems for low-latency, efficient, high-quality live streaming and transferring validated results toward production.

What you'll do

  • Develop and evaluate video coding and processing algorithms, including perceptual-quality methods, on heterogeneous platforms.
  • Optimize live-streaming encoding and decoding frameworks for latency, efficiency, and quality; benchmark, profile, and debug codec components.
  • Document research findings and collaborate with scientists and engineers to validate and transfer promising work to production-oriented workflows.

What they ask for

  • Currently pursuing a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related technical field.
  • Strong foundations in algorithms, data structures, computer systems, and software engineering.
  • Good understanding of image/video compression fundamentals and related research topics.
  • Strong programming and debugging skills in C/C++ or similar general-purpose programming languages.

Nice to have

  • Research experience in video compression, image/video processing, multimedia systems, or realtime communications.
  • Familiarity with video coding standards, neural-network-based visual methods, SIMD/NEON, multithreading, or live-streaming applications.

Tools

C/C++, AVS, H.264/AVC, H.265/HEVC, VVC, AV1, SIMD/NEON

AI focus

Research and development of machine-learning-based video coding and processing, including neural-network-based methods and multimodal models to improve coding decisions.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)