Want to define how AI generates coherent video over minutes, not seconds?
This role sits at the heart of one of the hardest open problems in generative media: long-form video generation!
You’ll join a small, research-driven team building a multi-modal foundation model that reasons jointly across image, text, and audio. Their work powers a creative platform used to generate controllable, expressive video - and the underlying model is already in production.
As a Research Scientist focused on long video generation, you’ll work on the architectural problems that emerge once sequences stop being toy-length.
You’ll spend your time pushing sequence models to handle multi-minute videos without collapse.
What you’ll work on
- Architectures for long-form, auto-regressive video generation
- Causal attention and long-context modelling strategies
- Techniques for temporal and semantic coherence over extended sequences
- Memory-efficient transformers and sequence compression
- Translating research into production-grade pipelines
- Publishing and presenting work internally and externally
You’ll fit well here if you’re comfortable operating at the intersection of theory and systems.
Someone who can read the latest long-context papers, prototype quickly in PyTorch, and reason about what scales when models move from experiments to real users.
The team works fully in-person in San Francisco or New York.
What you’ll bring
- PhD or equivalent research/industry experience in ML or sequence modelling
- Deep understanding of transformers, attention, and auto-regressive generation
- Experience with long-context or memory-efficient modelling
- Strong Python and PyTorch skills
- Evidence of real research impact or large-scale deployment
Package
- Salary: Negotiable depending on experience
- Meaningful equity
- Medical, dental, and vision cover
- 401(k)
- Lunch and snacks provided
- Fully in-person role (SF or NYC)
If you want to work on long-form video generation problems, this is one of the few places doing it properly - please apply now!
All applicants will receive a response.
| Location: | New York, NY |
|---|---|
| Job type: | Permanent |
| Emp type: | Full-time |
| Salary type: | Annual |
| Salary: | negotiable |
| Job published: | 17/12/2025 |
| Job ID: | 32690 |