VP/Head of Global Data Partner Network & Operations
Listed on 2026-09-29
-
IT/Tech
-
Business
Location:
San Francisco Bay Area / Silicon Valley
Full-time | In-person / Hybrid
COO-track leadership role
About Deep ReachDeep Reach is building the global real-world data network for Physical AI.
As AI moves from understanding the digital world to operating in the physical world, foundation models and world models need massive amounts of diverse, high-quality real-world interaction data.
Deep Reach builds the infrastructure and global network to make that possible.
Our Data Partner network includes Data Preneurs, AI data companies, businesses with access to real-world environments and skilled work forces, and specialized individuals and teams across multiple countries.
Instead of building a centralized data collection workforce, Deep Reach enables local partners to turn their environments, workforce, expertise, and operational capabilities into scalable data infrastructure for Physical AI.
We are an AI-native startup moving extremely fast, working with frontier AI companies and building a global network from day one.
The RoleWe are looking for a builder to own and scale Deep Reach’s global Data Partner network.
This is not a traditional operations role.
You will build the operating system behind a decentralized global network of entrepreneurs, companies, skilled-workforce organizations, and individual Data Partners.
You will be responsible for both network expansion and network operations — finding the right partners, activating them, helping them build local capacity, deploying new data collection infrastructure, maintaining quality, and turning distributed real-world environments into reliable data capacity.
Today, many of these functions are founder-driven.
Your job is to turn them into a scalable global machine.
The right person could grow into a broader COO leadership role as the company scales.
What You Will BuildYou will own the growth and operations of Deep Reach’s global Data Partner ecosystem.
- Recruit and develop Data Preneurs who can build local data businesses on top of Deep Reach.
- Identify and onboard AI data companies and professional data collection organizations.
- Build partnerships with companies that control valuable real-world environments or skilled work forces.
- Develop networks of specialized individuals and teams in industries relevant to Physical AI.
- Launch and operate Data Partner networks across the U.S., Latin America, Europe, Asia, and other markets.
- Build regional and country-level leadership structures instead of managing every partner centrally.
- Design qualification, certification, onboarding, training, incentive, payment, reputation, and performance systems.
- Create repeatable country-launch and Data Partner playbooks.
- Coordinate deployment of cameras, sensors, wearables, and future data collection hardware across the network.
- Translate customer data requirements into executable capacity across countries, environments, partners, and devices.
- Work closely with engineering and AI teams to continuously improve data quality, QA, automation, and partner productivity.
- Build dashboards and operating systems around capacity, utilization, acceptance rate, cost, quality, retention, and partner performance.
- Identify bottlenecks quickly and personally drive solutions when systems break.
- Help transform the network from hundreds of Data Partners into thousands of entrepreneurial and institutional nodes capable of supporting tens of thousands of devices globally.
We care much more about what you have built than what title you previously held.
You are likely someone who:
- Has a strong builder mentality
, you would rather create the system than inherit one. - Has an entrepreneurial personality and is comfortable operating with ambiguity.
- Has built something from 0 → 1 and then helped scale it…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).