Research Scientist, Video Foundation Models
Research Scientist developing large-scale native video and multimodal foundation models across architecture, training, evaluation, post-training, and inference. The role requires deep generative-modeling expertise and hands-on experience with distributed training of large-scale models.
About the job
Responsibilities
- Research, develop, and scale native video and multimodal foundation models through prototyping, large-scale pre-training, continued training, and post-training.
- Explore model architectures, training objectives, and conditioning mechanisms for video generation, reference- and memory-based generation, multimodal interaction, and joint audio-video generation.
- Build and improve large-scale data curation, distributed training, evaluation, and post-training pipelines.
- Design systematic experiments covering model scaling, generation quality, controllability, consistency, robustness, and inference efficiency.
- Collaborate with researchers, engineers, and product teams to shape the technical roadmap and translate model advances into real-world capabilities.
- Contribute to research publications and open-source releases when appropriate.
Requirements
- Strong research and engineering experience in generative modeling, including diffusion models, flow matching, DiTs, video generation, multimodal models, or world models.
- Hands-on experience training and evaluating large-scale image, video, or unified multimodal models with modern deep learning frameworks and distributed training systems.
- Track record of developing impactful models or systems through research publications, open-source contributions, production impact, or other significant technical work.
- Ability to independently own ambiguous research problems, move from ideas to experiments, and collaborate effectively.
- Specialized depth in one or more foundation-model areas, including model architecture, data curation, controllable generation, multimodal understanding and conditioning, post-training, reward modeling, model acceleration, inference systems, or deployment.
Compensation and Benefits
- Annual base salary: $200,000–$320,000.
- Company equity.
- Medical, dental, and vision insurance with 99.99% of premiums covered.
- 42 days of paid time off, including PTO, sick days, company holidays, and floating holidays.
- Generous parental leave and fertility support.
- 401(k) retirement savings plan.
- $500/month lifestyle spending account.
- Complimentary lunch and snacks for in-office employees.
- One Medical membership.
Skills
Generative Modeling, Diffusion Models, Flow Matching, Dits, Video Generation, Multimodal Models, World Models, Deep Learning, Distributed Training, Model Architecture, Data Curation, Reward Modeling, Inference Systems, PyTorch
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