What You'll Do This opportunity involves both the “science” and “engineering” parts of research, so feel free to choose the title you think is appropriate for you (Research Scientist or Research Engineer).

This is a multi-stack opportunity where you will work on the intersection of modeling, data, systems, and evaluation.

• Modeling: Architect large-scale video and audio generative models, focusing on strong temporal coherence and high perceptual quality.
• Data: Design, implement, and run robust data pipelines for curating, filtering, and captioning massive video and audio datasets.
• Systems: Train large-scale video and audio generative models on massive datasets and GPU clusters.
• Evaluation: Define and build novel evaluation frameworks to measure realism, temporal consistency, controllability, and human-aligned creative quality.

Who You Are

• Strong foundation in machine learning and generative modeling, with experience in video, audio, or multimodal domains.
• Deep understanding of autoregressive, diffusion/flow-based, or hybrid generative models, and their tradeoffs for long-horizon generation.
• Hands-on experience with PyTorch and large-scale training (distributed, mixed precision, large datasets).

What Sets You Apart (Bonus Points) Experience in the following around data, modeling, or evaluation:

• Text-to-video/audio models
• Vision language models
• Audio language models

Your application are reviewed by real people.