Music Generation Research Engineer

Hanging the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity

Music is at the heart of a large class of creative endeavors and an integral part of content creation. To help everyone create compelling videos, podcasts, and more, we are re-imagining music technology with generative AI to dramatically simplify the music creation process. We are looking for a research engineer (junior or senior) that is passionate about music generation, inference and post-training pipelines/algorithms, data annotation/collection, reinforcement learning, high-quality infrastructure and code-quality, and/or related foundational model training, inference, and data work.

What you'll do

• Drive high-quality system design for modelling engineering and productization efforts.
• Develop production inference algorithms, pipelines, and APIs with cross-functional teams.
• Develop evaluation infrastructure, metadata annotation, and/or related benchmarking.
• Work together with other researchers, engineers, and product partners for real-world impact.
• Iterate on technologies that you invent and work with product teams to productize your work.
• Engage with the scientific community, publish papers, and file patents based on your research.

What you need to succeed

• Masters, PhD degree, and/or record of exceptional ability.
• Exceptional "engineering generalist" skills and/or large-scale model training or deployment.
• Experience in music and audio AI.
• Hands-on experience with machine learning frameworks and models.
• Deep insight into real-world audio applications
• Ability to convert a research idea/paper to code in Python.
• Strong communication, teamwork, and collaboration skills.