Jobs at David AI

Build polished, performant frontend interfaces for audio-data products. Ship production-grade UI features, surface LLM/DSP-driven insights, iterate with researchers and operations, and scale interfaces for thousands of users.

Design and build scalable backend systems, APIs, and data processing pipelines for terabytes of audio. Deploy and evaluate LLM and DSP-based solutions, iterate with researchers, and maintain production-grade infrastructure supporting data collection and user-facing features.

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.

Lead full-stack feature development, build scalable systems processing terabytes of audio, deploy and evaluate LLM/DSP solutions, drive research iteration for data collection, mentor engineers, and establish technical standards while shipping production-grade user experiences.

Build and ship full-stack features and scalable data-processing pipelines for terabytes of audio; deploy and evaluate LLM/DSP solutions; iterate quickly with researchers and operations to collect and surface high-quality audio dataset insights.

The Senior Backend Engineer will design and maintain backend services, build scalable APIs, and optimize systems handling large audio data sets.

As a Deployment Strategist, you will partner with customers to shape audio AI strategies, leading projects from ideation to execution while fostering strong relationships. You'll work with technical teams to ensure high-quality outcomes and identify opportunities for implementation.

Own and scale David AI's global contributor network: acquire, activate, retain, and optimize contributors through experiments, product/incentive iteration, funnel optimization, and cross-functional partnership with Product, Operations, and Engineering.

As a Senior Machine Learning Research Engineer, you will research and implement advanced audio ML models, develop inference algorithms, and collaborate with the Operations team to enhance model quality.

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.