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David AI is the first audio data research company, bringing R&D rigor to dataset development for AI training. Founded in 2024 by former Scale AI engineers, the company has rapidly grown to serve most FAANG companies and AI labs as customers, recently raising a $50M Series B from top-tier investors including NVIDIA, Meritech, and First Round Capital.
The Technical Product Manager role focuses on owning a core part of David AI's Data Factory—the systems that transform raw audio into high-quality training data. Depending on background and organizational needs, this could span the contributor marketplace, operations infrastructure, new business units, or ML-facing systems.
Key responsibilities include:
- Owning strategy and roadmap for your Data Factory area, from 0→1 prototypes through production scale
- Leading complex operational efforts and designing workflows and automation for scale
- Building first versions yourself using scripts, SQL queries, dashboards, and prototypes, then partnering with engineering for scaled implementation
- Translating customer model requirements into concrete workflows and project plans
- Partnering across Operations, Engineering, and Research to prioritize problems and move systems from idea to deployment
- Using data to guide decisions, diagnose issues, and measure performance against throughput, quality, and cost metrics
- Taking full-stack accountability across product, operations, engineering, and customers
Ideal candidates have a CS or STEM undergraduate degree (or equivalent work experience), 2-8 years in product, operations, consulting, or startups, and direct experience as a PM, technical program manager, founder, or technical operator. Strong SQL proficiency and ability to build lightweight end-to-end prototypes are essential. You should have a track record of building operational tools, moving business problems from data foundation through analysis to implementation, and thinking systemically about scale and durability. High execution, attention to detail, strong product intuition, and collaborative low-ego approach are core to success.
