About our Research teamOur Research 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 roleAs a
Research Engineer at David AI, you'll build algorithms and systems that turn large-scale speech and audio collections into high-quality datasets. You'll tackle questions like: What makes a recording useful? How do we measure and improve dataset quality?
In this role, you will- Design algorithms and metrics using advanced signal processing algorithms and cutting edge ML models with to derive insights from thousands of hours of audio data.
- Build scalable data processing pipelines for analyzing, filtering, deduplicating, and curating large speech and audio datasets.
- 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- 3+ years of professional engineering or applied research experience in areas such as data systems, algorithms, applied ML, information retrieval, or speech and audio.
- Strong Python skills and experience building maintainable, production-quality software.
- End-to-end ownership of ML pipelines, from proof-of-concept to production deployment.
- Ability to translate research papers and ideas into high-quality, production-ready code.
- Experience deploying ML systems for production inference with cloud technologies.
- Ability to assess model quality in the context of user experience and business value.
Bonus points if you have- Experience with speech, audio, or digital signal processing.
- Experience with data curation, search and retrieval, embeddings, clustering, deduplication, or sampling.
- Experience building model inference systems or integrating pretrained models into production workflows.
- Experience in publishing in top conferences such as NeurIPS, ICML, ICLR, CVPR, etc.
- Experience in releasing, maintaining, contributing to open-source softwares.
- PhD or Masters in Computer Science or a related field.
Benefits- Unlimited PTO.
- Top-notch health, dental, and vision coverage with 100% coverage for most plans.
- FSA & HSA access.
- 401k access.
- Meals 2x daily through DoorDash + snacks and beverages available at the office.
- Unlimited company-sponsored Barry's classes.
