Research Product Manager

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.

Our Product team works at the intersection of research, engineering, and operations to shape audio data products that power modern machine learning models. We translate emerging research into thoughtful, scalable data products, ensuring quality, coverage, and clarity for model builders.

As an Product Manager on the Product team, you will own the strategy and execution for critical parts of our audio data portfolio. You will work closely with Research, ML, Engineering, and Operations to translate model needs into concrete data roadmaps, quality frameworks, and customer-ready deliverables.

• Based on interest and background, specialize in specific areas such as data roadmap and expansion, data quality and metrics, and/or evaluation and commercialization.

• Own product strategy and roadmaps for audio data products, from research-driven experimentation through scaled production and delivery for model builders.

• Translate researcher model training needs into precise requirements for data collection, quality standards, evaluation, and documentation.

• Partner closely with Research, ML, Engineering, and Operations to operationalize new datasets and capabilities.

• Define metrics and success criteria to guide prioritization and measure impact across quality, coverage, cost, and speed.

• Undergraduate degree in Computer Science, Engineering, Data Science, or a related field.

• 4+ years of experience in product management, data platforms, ML infrastructure, or adjacent technical roles.

• Direct experience working across engineering, operations, and research or ML teams.

• Strong technical intuition around data pipelines, annotations, evaluation, and ML training workflows.

• Analytical and structured, with the ability to turn ambiguous problems into clear plans and tradeoffs.