Jobs at David AI

Turn business data into decisions by identifying high-impact problems, defining company-wide metrics, conducting A/B experiments, building reliable ETL pipelines and data models, and delivering analysis, forecasting, dashboards, and modeling. Partner cross-functionally with product, engineering, research, operations, and go-to-market teams to shape priorities and ensure trustworthy, well-documented data.

Partner with customers on audio AI initiatives from ideation through launch. Build consultative relationships, translate customer objectives into actionable strategies with research and engineering teams, identify account opportunities, and execute strategic account plans that align stakeholders, advance complex opportunities, and drive long-term customer success.

Lead design, build, and scale end-to-end audio data pipelines from prototype to production. Collaborate with researchers, engineers, and cross-functional teams to ensure high throughput, quality, and cost-efficiency, monitor pipeline health, and drive improvements using metrics.

Own strategy and roadmap for a core part of the Data Factory, from prototypes to production. Lead and automate complex operational workflows, build MVPs (scripts, queries, dashboards), partner with Operations, Engineering, and Research, translate model capabilities into requirements, use data to measure throughput/quality/cost, and take full-stack accountability for product, operations, and customer outcomes.

Own end-to-end sourcing strategy for technical, product, and business roles. Build boolean search strings, talent maps, and market research. Run outbound outreach campaigns, maintain pipelines in Ashby, track sourcing metrics, and partner with hiring managers and recruiters to convert passive candidates into qualified pipelines.

Owns quality operations for all datasets, establishing global quality standards, calibration, review structures, language coverage, capacity planning, and contingent workforce sourcing. The role also manages dashboards tracking quality, throughput, and cost efficiency across international data operations. Candidates should have extensive operations leadership experience, quality management expertise at scale, and experience building tooling and workforce systems. Speech, audio, or linguistic data experience is preferred.