About the role
About our Machine Learning team
Our Machine Learning team sits at the intersection of cutting-edge research and production systems, transforming raw audio into high-signal data for leading AI labs and enterprises. We own the full ML lifecycle - from researching novel speech processing algorithms to deploying models processing terabytes of audio daily.
About this role
As an Applied ML Engineer at David AI you'll build cutting-edge speech and audio models, production inference systems and resilient pipelines that showcase what high-quality data can really do.
In this role, you will
- Research, design, and implement solutions using advanced signal processing. algorithms and bleeding edge ML models with application to speech and audio.
- Develop production-grade inference algorithms, pipelines, and APIs with cross-functional teams that unlock key insights into our data for our customers.
- Collaborating with our Operations team to gather useful training and evaluation datasets to improve the quality of our models.
- Architect systems that enable resilient, durable inference and evaluations.
Your background looks like
- 5+ years of professional audio ML experience, including DSP and ML audio algorithm development.
- End-to-end ownership of ML pipelines, from proof-of-concept to production deployment.
- Strong coding skills in Python and proficiency with deep learning frameworks such as PyTorch.
- Ability to translate research papers and ideas into high-quality, production-ready code.
