Research Engineer - Audio & Speech Models

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 autoencoders, ASR, TTS, SSL, and speech-to-speech models. You will be deeply involved in the entire model training process, from data gathering and processing to designing novel architectures and training methodologies.

Large-scale audio training runs

Performance optimization of our training stack

Audio dataset collection, processing, and evaluation

Architecture and training methodology ablations and improvements

Our research methodology is grounded in methodical, step-by-step approaches to ambitious goals. Both deep research and engineering excellence are equally valued

We strongly value new and crazy ideas and are very willing to bet big on new ideas

We move as quickly as we can; we aim to minimize the bar to impact as low as possible

We all enjoy what we do and love discussing AI

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

Excellent communication and collaboration skills, and can work effectively on both research and engineering implementation at scale

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

Proficiency with PyTorch and Python

Experience contributing to large pre-existing codebases and rapidly getting up to speed

Previously published machine learning research in well-respected venues

Postgraduate degree in a scientific subject (Computer Science, EE/EECS, Mathematics, Physics, Machine Learning)