Research Intern (Video Data Compression and Application) - 2026 Start (PhD)

About the Team

The Multimedia Lab at ByteDance aims to explore and lead cutting-edge technologies in the multimedia field, deeply participate in international multimedia standardization work, provide software and hardware solutions for multimedia content generation, analysis/processing, innovative interaction, and empower our business in various aspects.

Responsibilities

• Design, develop, and optimize innovative algorithms for data compression, processing, and large multimodal model applications, including but not limited to 2D video, multiview video, point clouds, Gaussian splatting–based or NN-based coding, token compression, and KV cache optimization.
• Stay up to date with state-of-the-art techniques through standardization activities or leading conference/journal publications.
• Build prototypes and demonstrations, and contribute to technical reports, publications, and patent filings.

Qualifications

• Minimum Qualifications: Current Ph.D. student in computer science/electrical engineering/mathematics/statistics/data science and related disciplines.
• Strong Computer Science fundamentals (algorithms, data structures, software design) and problem-solving skills.
• Familiar with token/image/video coding and processing or large multimodal models.
• Familiar with Python, PyTorch.
• Familiar with C/C++.
• Collaborative mindset, with solid written and verbal communication skills.

Preferred Qualifications

• Good understanding of state-of-art compression algorithms.
• Rich experience and interest in video/image coding standards (e.g., H.263/264/265/266, MPEG-2/4, JPEG, JPEG 2000, AV1, AV2, AVS1/2/3, etc.).
• Proficient in deep learning frameworks such as PyTorch, TensorFlow, and YOLO.
• Hands-on experience with large language models (LLMs) and vision-language models (VLMs), including LoRA, diffusion models, and VQA tasks.
• Experience with model training, fine-tuning, and evaluation pipelines.
• Familiar with GPU acceleration and CUDA environment configuration.