David AI

Coordinates recruiting workflows end to end, including interview scheduling, candidate communications, ATS management, and process improvement. The role requires at least one year of professional experience, excellent organization and communication, and onsite work five days per week.

Own strategy and execution for audio data products, translating research and model-training needs into scalable data roadmaps, quality frameworks, evaluation criteria, and customer-ready deliverables. Requires 4+ years in product management, data platforms, ML infrastructure, or a related technical field.

Owns strategy, prototyping, and scaled delivery for a core audio-data factory area, partnering across Operations, Engineering, and Research. The role requires strong SQL, technical prototyping, product judgment, and operational execution in complex startup environments.

Build scalable backend systems, APIs, and data pipelines that process large volumes of audio data and support AI research and customer-facing products. The role requires at least two years of backend engineering experience and strong systems fundamentals; ML, DSP, or audio expertise is a plus.

Build polished, scalable frontend interfaces that help users explore and understand audio data for AI model training. The role requires at least two years of frontend engineering experience and strong product-focused UI fundamentals.

Owns sourcing strategy and top-of-funnel pipeline generation across technical, product, and business operations roles. Requires 5+ years of sourcing experience, strong Boolean search and recruiting-tool expertise, and success filling hard-to-source positions.

Lead end-to-end data pipelines at David AI, turning raw audio into high-quality training datasets for frontier AI labs. Own prototypes to scaled production, collaborating with researchers, engineers, and ops teams while driving metrics on throughput, quality, and cost.

Lead full-stack development of scalable audio data platforms, building features and mentoring engineers in a fast-paced AI startup. Requires 6+ years of product-focused full-stack experience and technical leadership.

Build full-stack tools and scalable data pipelines for audio AI research. Work closely with researchers to iterate on data collection and processing interfaces.

Build cutting-edge speech and audio ML models, production inference systems, and resilient pipelines. Own full ML lifecycle from research to deployment on terabytes of audio data.

Leads end-to-end customer journeys for audio AI initiatives, builds consultative relationships with stakeholders, translates objectives into actionable strategies with research/engineering teams, and uncovers growth opportunities. Requires 4+ years experience, AI data familiarity, and strong project management.

Builds and maintains scalable backend services and distributed systems to process petabytes of audio data. Requires 3+ years backend experience with APIs, databases, cloud infra, and distributed systems.

Leads Data Operations team to build and scale audio data pipelines from experiments to production for AI models. Partners with researchers and executives, drives metrics-based decisions, and ensures high-quality data delivery at scale. Requires 5-10 years high-ownership experience and SQL proficiency.