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David AI · Hiring

Technical Product Manager

San FranciscoOn SiteFull Time$145K – $225K • Offers Equity

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 Technical Product Manager team

Our Technical Product Manager team builds the Data Factory at David AI. We set the strategy for how raw audio becomes high-quality training data, decide what gets built, and own the outcomes: scale, quality, cost, and the experience of our contributors. Working across Operations, Engineering, and Research, we move fluidly across all three to solve some of the most challenging problems at David AI.

About this role

David AI is hiring a Technical Product Manager to own a core part of our Data Factory, from early prototypes through production scale. Depending on your background and where we need you most, that could cover our contributor marketplace, our Operations infrastructure, a new or scaling business unit, or the systems our ML team relies on. You'll need the operational chops to lead complex efforts, the instinct to automate them, the technical ability to build the first MVP yourself, and the judgment to partner with engineering and research to implement at scale.

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