ML Program Lead
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 an ML Program Lead, you will work closely with our ML research team to define data annotation requirements and manage our team of audio engineering QAs to operationalize them and deliver audio model training datasets. You’ll need technical depth, an operator’s mindset, and the ability to manage a large, geographically distributed team of operators.
In this role, you will:
Work with ML researchers to identify and define audio events and acoustic quality issues (What counts as “muffled” audio? How do we define “robotic artifacts”?).
Turn these definitions into actionable guidelines for our expert audio QAs to label internal audio data.
Manage the QA team in a rapid iteration loop of labeling audio samples, getting feedback from ML researchers, and refining the annotation process to deliver high-quality training and eval sets.
Conduct quality audits on annotation and post-processing models before they land in production.
Your background:
3+ years in program or product management, consulting, or similar experience.
Technical foundation in CS, Engineering, or similar.
Experience in data collection and/or the ML model training process.
High-execution operator: organized, detail-oriented, and uncompromising on quality.
Excellent analytical and problem-solving skills with attention to detail; SQL required.
Systems thinker who can spot leverage points and design for scale and durability.
Strong product intuition; able to work with engineers and researchers to get to the correct answer.
Collaborative and low-ego; willing to roll up your sleeves.
Bonus points if you have:
Experience in audio engineering, sound mixing, or operating a sound board