Data Product Operations Lead
Company websitewithdavid.ai (David AI, opens in new tab)
Base salary $125K to $175K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA +1 more
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA +1 more
- WorkplaceOn-site
- Status at last checkSource accepting applications when checked
- Last checked (6 min ago) · observed since
All places named
- San Francisco, CA
- New York City, NY
About this job
About David AI
David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world, and we believe audio is the gateway. Speech is versatile, accessible, and human—it fits naturally into everyday life. As audio AI advances and new use cases emerge, high-quality training data is the bottleneck. This is where David AI comes in.
David AI was founded in 2024 by a team of former Scale AI engineers and operators. In less than a year, we’ve brought on most FAANG companies and AI labs as customers. We recently raised a $50M Series B from Meritech, NVIDIA, Jack Altman (Alt Capital), Amplify Partners, First Round Capital and other Tier 1 investors.
Our team is sharp, humble, ambitious, and tight-knit. We’re looking for the best research, engineering, product, and operations minds to join us on our mission to push the frontier of audio AI.
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
1–6 years in high-intensity environments (e.g. founder, strategy consulting, or venture-backed ops).
Background in strategy consulting, strategic projects, investment banking, operations, computer science, or similar
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.
Benefits
Unlimited PTO.
Top-notch health, dental, and vision coverage with 100% coverage for most plans.
FSA & HSA access.
401k access.
Meals 2x daily through DoorDash + snacks and beverages available at the office.
Unlimited company-sponsored Barry’s classes.
Source: David AI on Ashby · View original posting (opens in new tab)
This listingData Product Operations Lead$125K to $175K
Senior Technical Sourcer$140K to $170K
Deployment Strategist$145K to $175K
Technical Product Manager$145K to $225K
Head of Quality Assurance Operations$150K to $200K
Product Engineer, Backend$165K to $225K
Product Engineer, Full Stack$165K to $225K
Chart as a table
| Role | Published base |
|---|---|
| Data Product Operations Lead (this listing) | $125K - $175K |
| Senior Technical Sourcer | $140K - $170K |
| Deployment Strategist | $145K - $175K |
| Technical Product Manager | $145K - $225K |
| Head of Quality Assurance Operations | $150K - $200K |
| Product Engineer, Backend | $165K - $225K |
| Product Engineer, Full Stack | $165K - $225K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-07-22
Where this pay comes from
Location as the employer wrote it: San Francisco • New York City
USD 125,000 – 175,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
