Jobs at David AI

Partners with managers, leaders, and employees on performance, career development, employee relations, team structure, compensation, leveling, and talent decisions. Builds performance review and manager development programs, advises on sensitive workplace matters, and uses employee feedback and people data to identify retention and team-health risks. Supports People initiatives and helps scale the company’s HR function during rapid growth.

Own CRM management, pipeline forecasting, deal progression, and GTM operating rhythms. Build scalable GTM processes, reporting systems, AI agents, and workflow automations from scratch. Partner with founders and leadership on pipeline visibility, prioritization, and go-to-market planning while maintaining accountability across stakeholders in a fast-paced startup environment.

Lead legal strategy as David AI’s founding legal hire, advising executives on AI, data, privacy, commercial, transactional, corporate, and regulatory matters. Negotiate agreements with leading AI labs, manage external counsel, and build the company’s legal processes, infrastructure, and future team. The role requires 5–12 years of post-JD experience, elite law firm experience, strong commercial judgment, and familiarity with AI, data, or privacy issues.

Own full-cycle recruiting for critical engineering, research, and technical product roles. Partner with the CTO and engineering leaders on role definition, candidate assessment, interview processes, sourcing, engagement, negotiation, and closing. Build passive-candidate pipelines using talent mapping and Boolean search, maintain Ashby funnel data, improve recruiting operations, monitor technical talent markets, and deliver an excellent candidate experience.

Own the customer-to-data production feedback loop for audio AI models. Run experiments, ablations, and benchmarks; analyze model behavior; improve data collection, filtering, weighting, annotation, and QA; and build evaluation tooling and pipelines. Translate research findings and customer requirements into rapid product and production changes while collaborating with research engineers and technical stakeholders. Help shape experimentation practices, engineering culture, and the team roadmap.

Build and lead David AI’s marketing function, including company positioning, campaigns, editorial content, media and industry relations, founder communications, benchmark promotion, recruiting reputation, and team development. The role combines hands-on writing and storytelling with marketing strategy, budget allocation, cross-functional collaboration, and hiring. Candidates should be experienced in technical storytelling, audience development, communications, PR, community building, and leading marketing teams in fast-growing startups.

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.

Build algorithms, metrics, scalable pipelines, and production inference systems that analyze, filter, deduplicate, and curate large-scale speech and audio datasets. Translate research into production software, evaluate model and dataset quality, architect resilient ML systems, and collaborate with operations and cross-functional teams to improve customer-facing data products.

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.

Partner with the CEO to drive the company’s highest-priority initiatives from strategy through execution. The Chief of Staff will lead cross-functional projects, support company planning and operating rhythms, analyze business challenges, prepare board and fundraising materials, assist with executive hiring, and temporarily own initiatives until a long-term owner is established.

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.

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 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.

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.