Video Algorithm Engineer - Multimedia Lab

ByteDance ByteDance · Big Tech · San Jose, CA · R&D

The role focuses on designing and implementing algorithms for video systems, including encoding, understanding, processing, enhancement, quality metrics, delivery, and streaming. It requires strong CS fundamentals, programming skills, and experience in video-related areas, with a preference for deep learning and neural-network-based approaches.

What you'd actually do

  1. Design and implement adaptive video encoding algorithms at both internal and external codec levels
  2. Design and implement video understanding, and video processing and enhancement algorithms
  3. Design and validate image/video quality metrics, no-reference, and full-reference metrics
  4. Design and implement efficient video delivery and streaming algorithms for both Live and VOD services

Skills

Required

  • BS degree or above in Computer Science, Electrical Engineering, or equivalent fields
  • Strong Computer Science fundamentals (algorithms, data structures, software design) and problem-solving skills
  • Excellent programming, debugging, and optimization skills in one or more general-purpose programming languages including but not limited to: C/C++, Python, etc.
  • Strong knowledge and solid experience in one of the following areas: video understanding, video processing (denoise, super-resolution, HDR etc.), video coding, video streaming (DASH, ABR, QoE etc.), video quality assessment, and subjective visual quality optimization etc.
  • Collaborative mindset, with solid written and verbal communication skills

Nice to have

  • Familiar with video coding standards (AVC/H.264, HEVC/H.265, AV1, and VVC, etc.)
  • Experience in open-source multimedia projects (x264, x265, and FFMPEG, etc.)
  • Experience in video-related applications, such as short video streaming, video transcoding, live streaming, etc.
  • Experience in deep learning and neural-network-based video coding/processing/streaming algorithms
  • Experience in algorithm optimization on CPU, GPU, and mobile platform, etc.

What the JD emphasized

  • deep learning and neural-network-based video coding/processing/streaming algorithms

Other signals

  • video understanding
  • video processing
  • video coding
  • video streaming
  • video quality assessment
  • deep learning
  • neural-network-based video coding/processing/streaming algorithms