As a Video Generation Research Intern, you will work closely with our research and engineering teams to advance post-training techniques for large-scale video generation models, with a particular focus on controllability, generation quality, and temporal consistency.

Research, develop, and implement post-training methods for video generation models, including supervised fine-tuning, preference optimization, and reinforcement learning-based approaches.

Explore controllable video generation techniques to improve motion control, camera movement, trajectory following, and action-conditioned generation.

Design and conduct experiments to improve video generation quality, temporal consistency, motion realism, and alignment with user instructions.

Collaborate with researchers and engineers to develop training pipelines, evaluation benchmarks, and scalable experimentation workflows.

Stay up to date with the latest advances in video generation and generative AI, and contribute to research publications and practical applications.

What We Are Looking For

Currently pursuing a Master's or PhD degree in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, or a related technical field.

Strong research background and hands-on experience in video generation, including training or fine-tuning video generative models.

Solid understanding of modern generative modeling techniques, such as diffusion models, flow matching, Diffusion Transformers (DiTs), and autoregressive models.

Strong proficiency in Python and deep learning frameworks such as PyTorch.

Ability to independently implement research ideas, conduct experiments, analyze results, and collaborate effectively with a research team.

Research Scientist Intern - Video Generation

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Hoyoverse

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