Description
We are seeking a Staff Research Engineer to join our Artist-First AI Music lab.
Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives.
All of our products will put artists and songwriters first, through four key principles:
- Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.
- Choice in participation: We recognize there’s a wide range of views on use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.
- Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for uses of their work and transparently credited for their contributions.
- Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans.
As a Staff Research Engineer, you will work side-by-side with research scientists to conduct groundbreaking research in music generation, improve model training pipelines, optimize performance, integrate models into production environments, and maintain a high-quality codebase.
You will have experience training or fine-tuning large machine learning models on GPUs using PyTorch or similar frameworks, working with cloud platforms like Google Cloud Platform, AWS, or Microsoft Azure, and debugging problems in machine learning training code.
You will also communicate effectively with global teams and be ready to work both face-to-face and asynchronously with collaborators on multiple continents.
If you are resourceful and proactive, enjoy learning new concepts and technologies quickly, and are not afraid to dig deep into the stack, we encourage you to apply for this role.