Data Acquisition Lead, Frontier Environments

Scale AI•San Francisco, CA

3d•$182,400 - $228,000•Remote

About The Position

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead, you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams.

Requirements

5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there
A strong track record of managing important external relationships
Strong business judgment and the ability to evaluate partnership value quickly
Clear communication skills and comfort working with senior stakeholders
Ability to operate independently while staying closely connected to cross-functional teams
A practical, hands-on approach to building new functions from the ground up
Comfort working in fast-moving, ambiguous environments

Nice To Haves

Experience in AI, data infrastructure, marketplaces, platforms, or high-growth technology companies
Familiarity with post-training, RL, evals, or synthetic data
Experience with data licensing, IP, or regulated data
Experience partnering closely with Legal and Finance on complex agreements

Responsibilities

Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order.
Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced.
Close. Own it from cold outreach to signature.
Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable.
Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline.