David AI is a San Francisco-based research lab that builds large, diverse audio datasets to power next-generation speech and voice AI models.
ABOUT DAVID AI David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human—it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in. David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors. Our team is sharp, humble, ambitious, and tight-knit. We’re looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI. 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 a ML Research 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 cutting 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. - Experience deploying ML systems for production inference with cloud technologies. - Track record of setting ML roadmaps, influencing technical direction, and prioritizing research and infrastructure investments. - Ability to assess model quality in the context of user experience and business value. BONUS POINTS IF YOU HAVE - PhD or Masters in Computer Science or a related field. - Experience training large neural network models in academic or industry settings. - Expertise in audio signal processing both classical and machine learning techniques. - Experience in publishing in top conferences such as NeurIPS, ICML, ICLR, CVPR, etc. 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.