Data Operations - World Model Lab

Vendor Operations & Technical Account Manager, Data

Up to $350k + Equity

Our client is building real-time world models AI that simulates reality rather than generating clips of it. They just raised one of the largest rounds in the category, and 50+ data vendors are knocking on their door. Nobody owns that door. That's this job.

The role

The mandate is to 10x the lab's data estate across six-plus modalities, from web-scale video to high-fidelity robotics demonstration data, over the next four quarters. You'll build and run the entire vendor operation: qualify the landscape, negotiate terms, and maintain the operational muscle to execute acquisition and delivery deals in parallel. You'll know what a dataset should cost, why one vendor's collection methodology beats another's, and how to structure an agreement when no one can forecast volume yet.

What you'll do

• Map and qualify the vendor landscape: engage the top 2–3 vendors per data category; keep the rest deliberately warm
• Negotiate contractual terms, end-to-end pricing models, quality SLAs, delivery terms, and SOW and contract review
• Build optionality into agreements: structures that let the lab return in a month, ready for 2x volume, without renegotiating from scratch
• Maintain a living vendor directory and run multiple acquisition deals in parallel
• Own commercial relationships as spend scales: performance management, escalation, renegotiation
• Build the vendor management playbook from scratch; this is the lab's first dedicated commercial data seat

What you bring

• Real commercial ownership of data or technical services: you've priced engagements, negotiated terms, redlined SOWs, and managed delivery against them
• Vendor-side experience at a data provider serving AI labs, a consulting delivery background (manager/senior manager at the Accenture/Deloitte/EY tier), or buy-side procurement of custom datasets
• Enough technical fluency to judge how data is produced and whether it's worth the price
• Operational ability to run many workstreams in parallel without compromising quality
• Bay Area-based or relocating to the Bay Area, where the vendor ecosystem lives

Bonus: delivery/engagement leadership at an AI training-data vendor; technical foundation before consulting; robotics, video or multimodal data exposure.