Ooak Data turns company data into training data for AI agents.
Frontier labs can train models to reason. They cannot train them to work: navigating a real company's Slack threads, half-finished Notion docs, contradictory Jira tickets, and permission boundaries. That requires real enterprise data, and you cannot synthesize it. You have to source it.
We plug into enterprise tools, anonymize everything into a structurally identical digital twin, and generate reinforcement-learning environments with expert-level tasks calibrated against frontier models. Three weeks from raw company data to an RL-ready environment, three times faster than at launch.
We are a Y Combinator company with signed contracts with three frontier AI labs, and we are scaling delivery aggressively over the next twelve months. Three founders, full-time since December 2025: Pierre-Louis (CEO, ex-COO in edtech, sold data to frontier labs), Grégoire (CPO, first PM at Epsor through Series B), Thomas (CTO, ex-Head of Data at PayLead, ex-Samsung AI lab).
We were 4 in June. We are 16 today, and we should be around 25 by Christmas.
So far every hire has been screened, often sourced, and always closed by one of the three of us. We loved doing it. But at this pace it pulls us away from product, engineering and customers, and it makes us slower to answer people than we want to be.
Speed matters. What matters more is who we become. The team we build over the next twelve months is the company. Every hire either strengthens what we stand for, trust, ambition, collective, kindness, or quietly waters it down. Someone has to hold that line with us: in who we go after, in the hard calls, in how people are welcomed, how they grow, and why they stay.
We are looking for a Head of People to build that team with us. The one people will want to join, and grow in.
Hiring, end to end
Employer brand
The team we become
The people foundation
You have done this before. You have run People in a startup or scale-up that grew fast while you were there, and you know what crossing 50 people does to a company. Maybe you built the function from a blank page, maybe you scaled one. What matters to us: you have closed hard profiles yourself, and you have stayed close to a team through the good weeks and the hard conversations.
And you want to give a lot to build an ambitious, fast-growing company where people are glad to come in on a Monday.
Bonus points if you have hired for an AI or data company and know what a good ML engineer looks like on paper and in a call.
Ooak Data (YC S26) builds the data infrastructure that frontier AI labs use to train and evaluate their agent models. They collect enterprise data from real company tools — Google Drive, Slack, Gmail, Notion, Jira, SharePoint, Teams, emails, videos, images — anonymize it, and turn it into RL environments and digital twins for agent training. Their core product, Alexandria, is designed to be the world's largest library of real-world business workflow datasets. They're also growing into "enrichment" — creating task ecosystems that let labs train models directly on real-world multi-step workflows, not just receive raw data. Signed large purchase orders with frontier AI labs (not SaaS), now in delivery mode. Data anonymization pipeline has been reduced from ~1 month to ~2 weeks per client.
Salary
$70,000 - $90,000
Equity
0.1% - 0.5%
Location
Paris, Paris
Experience
6+ years
Last stage
Seed
Investors
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.