Research Engineer

What you’ll do Work on generative audio systems across models, evaluation, and data Design experiments that separate genuine progress from noise Build evaluation and dataset pipelines that make model quality measurable and iteration faster Make sound trade-offs across quality, latency, reliability, and cost What we’re looking for Comfort taking ownership in ambiguous problem spaces and staying engaged with the problem until it is solved Genuine interest in audio, music, and generative modeling Strong habits around evaluation, reproducibility, and performance Fluency in Python and PyTorch, or similar tools Especially relevant experience Generative modeling, including diffusion, autoregressive methods, or hybrids Audio ML, or adjacent experience that transfers well, such as image generation Multi-GPU or distributed training What we offer High ownership over important technical work Be at the forefront of AI-driven music innovation Opportunity to work on infrastructure at scale Competitive compensation and equity Flexibility in how you work