Role overview
As an Audio Machine Learning Engineer, you will focus on solving challenging problems related to AI-based vocals and audio engineering. You will collaborate closely with the AI team to design, develop, and improve large-scale machine learning models for audio applications.
You will play a key role in researching new approaches, building production-ready models, and continuously improving existing systems using modern machine learning techniques.
What you'll work on
- Researching, developing, and improving machine learning models for singing voice synthesis (SVS) and voice conversion
- Experimenting with diffusion-based generative models for vocals and audio
- Working with neural vocoders (e.g., HiFi-GAN–style architectures, large-scale GAN-based or diffusion-based vocoders)
- Designing and improving audio feature extraction pipelines for vocal modeling
- Working with large, high-quality vocal and music datasets
- Improving model quality, robustness, and inference performance
- Integrating new models and improvements into production systems
- Writing clean, efficient, and scalable Python code using **PyTorch
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Remote Ai Machine Learning