Data Product Operations Lead
San Francisco, CAFull-timeSeen 1mo agoStill listed 4w ago
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Job overview
The Data Operations team at David AI builds and scales data pipelines that transform raw audio into high‑quality training datasets for leading AI labs, requiring a hands‑on leader to own end‑to‑end pipeline success, design for reliability and efficiency, and collaborate across ops, product, and engineering.
Skills & qualifications
Skills
Benefits
Full job description
About our Data Operations team Our Data Operations team powers David AI's Data Factory, transforming raw audio into high-quality training datasets for leading AI labs. Our mandate is to spin up new data pipelines and run them at a massive scale. This means starting from a model capability we want a model to unlock, experimenting with different shapes of data and collection strategies, and validating them with researchers. Once an approach works, we industrialize it, building pipelines that can process audio with reliability, quality, and efficiency. We are relentless operators who thrive in ambiguity, equally comfortable prototyping novel workflows as we are managing large-scale production systems. About this role As a Data Product Operations Lead, you’ll help drive David AI’s Data Factory — designing and scaling the pipelines that turn raw audio into high-quality datasets for frontier AI labs. You’ll take ownership of data products from 0→1 prototypes through 1→N scale, working hands-on to build workflows, validate them with researchers, and run them reliably at production scale. In this role, you will
- Own end-to-end success of a data pipeline, from early experiments to scaling up production systems that generate high-quality audio data at high volumes.
- Design and run pipelines that process a high volume of audio data with reliability, quality, and efficiency.
- Work with researchers at leading AI labs to identify new model capabilities and turn them into concrete data workflows and project plans.
- Lead cross-functional workstreams across Ops, Product, and Engineering to build scalable “data factory” systems.
- Monitor and improve pipeline health, spotting and fixing issues in sourcing, quality, or process.
- Drive impact with metrics, using throughput, quality, and cost to prioritize and improve.
- Take full-stack accountability across operations, product, engineering, and customers, solving bottlenecks and ensuring delivery.
Your background looks like
- 2–6 years in high-intensity environments (e.g. founder, strategy consulting, or venture-backed ops).
- Technical foundation in CS, Industrial Engineering, or similar; SQL required.
- Systems thinker who can spot leverage points and design for scale and durability.
- Strong product intuition, able to work with engineers and researchers to get to the right answer fast.
- High-execution operator: fast, detail-oriented, and uncompromising on quality.
- Collaborative and low-ego, willing to roll up your sleeves.
Bonus points if you have
- A track record of extreme ownership, caring about outcomes over tasks.
- Experience in data, ML, or large-scale operations.
Compensation and benefits
- Rapid career growth at one of the fastest growing Series A companies, within a new and booming industry.
- Competitive salary and equity package.
- Flexible PTO policy.
- Top-notch health, dental, and vision coverage with 100% company reimbursement for most plans.
- Paid lunch and dinner in the office, every day through DoorDash.
- 401k access.
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