About
Stealth generative AI startup building foundation models for music. The team has secured licensing agreements with major record labels and publishers and is moving into large-scale model training and product execution. The company operates fully remote across the US and Europe.
What you'll do
- Train and improve large-scale generative models for music, with focus on diffusion-based approaches
- Design and run experiments across architecture, objectives, and data strategies
- Own the full model lifecycle: dataset curation, preprocessing, training, and evaluation
- Collaborate closely with a small research team to push model quality
- Contribute to infrastructure and MLOps decisions supporting large-scale training
- Operate with broad scope and high ownership in a startup environment
What you'll need
- Hands-on experience training diffusion models
- Strong background in large-scale model training and deep learning research
- 2+ years of research experience post-PhD or equivalent industry experience
- Solid engineering skills and experience owning training pipelines end-to-end
- Experience from a rigorous AI research environment preferred
- Ability to thrive in a small, fast-moving team
Shortlisted candidates will be contacted within 48 hours.
