Research Engineer – Audio & Speech Models

Zyphra•Palo Alto, CA

18h•Onsite

About The Position

As a Research Engineer - Audio & Speech Models , you will be a core contributor on Zyphra’s Audio Team, building the next generation of open-source text-to-speech and audio models. You will be deeply involved in the entire model training process from data gathering and processing to designing novel architectures and training methodologies. You’ll work across: Large-scale audio training runs Performance optimization of our training stack Audio dataset collection, processing, and evaluation Architecture and training methodology ablations and improvements

Requirements

Strong research taste and intuition.
The ability to work through a research project from conception to execution to write-up.
Strong implementation and prototyping ability (can take an idea from conception to experimentation quickly)
The ability to work well with others in a high-paced research setting
Can rapidly learn new fields and are excited to implement new ideas
Excellent communication and collaboration skills, and can work effectively on both research and engineering implementation at scale.
Proficiency with PyTorch and Python.
Experience contributing to large pre-existing codebases and rapidly getting up to speed.

Nice To Haves

Expertise and intuition for training models in the audio domain, including text-to-speech, ASR, speech-to-speech, speech-emotion-recognition, or other models
Experience in training audio autoencoders.
Understanding of signal processing, especially of audio signals.
Experience with diffusion models, consistency models, or GANs
Experience with training on large-scale (multi-node) GPU clusters
Strong grasp of proper experimental methodology for running rigorous ablations and other hypothesis testing
Understanding of and interest in large-scale, highly parallel data processing pipelines.
Previously published machine learning research in well-respected venues.
Postgraduate degree in a scientific subject (Computer Science, EE/EECS, Mathematics, Physics, Machine Learning)