Improving the quality of experience (QoE) for billions of users by designing and optimizing the next-generation end-to-end video system at ByteDance
Requirements
- In-depth knowledge of video analysis algorithms or subjective/objective video quality algorithms, and state-of-the-art technologies
- Proficient in one of the following: C, C++, Python
- Familiar with ML and image processing tools, including sklearn, opencv, ffmpeg, etc
- Familiar with deep learning frameworks (Tensorflow/Pytorch)
- Familiar with Transformer architectures and mainstream multi-modal large models (MLLMs), and hands-on implementation or research experience preferred
- Familiar with Linux development environments, shell scripting, HDFS etc
- Knowledge of common video processing algorithms, such as supperresolution, defusion model, etc.
Responsibilities
- Design video analysis (ROI/SOD, content understanding, temporal grounding etc.) and quality assessment algorithms, and participate in database creation, algorithm design/development/optimization, etc.
- Participate in designing strategy and solution for E2E video quality optimization with a combination of video analysis, processing and encoding algorithms
- Apply designed algorithms for VOD / Live streaming monitoring, data analysis, objective evaluation for algorithms etc.
- Collaborate with X-functional teams to integrate algorithms into production workflows and validate their impact through A/B testing
Other
- Currently pursuing a PhD in computer science/electrical engineering or a related technical discipline
- Great communication, eager to learn, and always passionate about turning cutting-edge technologies into real life use cases
- Ability to work in a dynamic internship experience with hands-on learning, enriching community-building and development events, and collaboration with industry experts
- Availability for a 12-week internship
- Clear statement of availability in resume (Start date, End date)
