About the role
structured by ORIBack Ooak Data Actively Hiring ### Data Quality Specialist Paris, Paris Full-time Visa Sponsorship ### About the role ### We're Ooak Data Ooak Data turns company data into training data for AI agents. Frontier labs can train models to reason.
What you will do
- Define the standard. Acceptance criteria, checklists, sampling methods, error thresholds.
- Audit what we ship. Processed and anonymized data, reviewed before delivery: PII leakage, replacement consistency, structural integrity, and whether the business value survived the anonymization.
- Automate your own job. Manual review does not scale. You write the detection scripts and the analyses yourself, and you work with the engineers to turn the ones that prove themselves into production checks.
- Measure and escalate. Quality metrics per dataset and per vendor, including the third parties we work with.
- Translate client requirements into specs. Work with the tech and sales teams to turn what a lab actually wants into concrete, testable quality criteria.
What they are looking for
- 4+ years in data quality, data operations, or QA, ideally at a data labeling company, a data provider, or an AI company.
- Hands-on with large, messy datasets: processing them, auditing them, finding what is wrong with them. Python and SQL are required: you write your own scripts to interrogate a dataset, you do not wait for someone to pull the data for you.
- Comfortable in a tech team. You will sit with engineers, read their pipeline, and hold your own in a technical conversation. You are not expected to ship production code, but you are expected to be credible.
- A track record of building quality standards from scratch, not just applying someone else's checklist.
- Obsessive attention to detail. You enjoy finding the error everyone else missed, and you are not satisfied until you understand why it was there.
- Systems thinking. When you find one error, your instinct is to ask how many others like it exist and how to catch them automatically.
- AI-first. You use LLMs and AI tools as daily leverage to audit, automate, and move faster.
- Fluent English, mandatory (working language with our partners and the labs).
Nice to have
- Familiarity with PII, de-identification, or privacy requirements.
- Exposure to annotation quality concepts: rubrics, inter-annotator agreement, guideline design.
- Understanding of how training data is actually used: SFT, RLHF, RL environments, evaluation.
- Experience working with external vendors or an annotation workforce.
Before you apply
- Visa Sponsorship
Benefits
- A function to build, not to inherit. Quality at Ooak Data is yours to define from the ground up.
- Your work is visible. What you validate goes straight to the largest AI labs in the world.
- Entrepreneurial adventure: founding impact, live the early days of an ambitious company at the front line of the AI revolution.
- Backed by Y Combinator, join just as we accelerate.
- Perks: Alan health insurance (mutuelle), 50% Navigo covered.
Full posting text
Back
Ooak Data
Actively Hiring
Data Quality Specialist
Paris, Paris
Full-time
Visa Sponsorship
About the role
We're Ooak Data
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.
We are a Y Combinator company with 8 figures contracts signed with frontier AI labs, and we are scaling delivery aggressively over the next months.
🤝 Our values
- Trust, the foundation of every relationship, internal and external. We extend it by default and value the ownership that comes with it.
- Ambition, we commit, we move fast, with tenacity and efficiency.
- Collective, team first, low ego.
- Kindness, at the heart of every interaction.
The offer
📍 Location: Paris (city center), on-site with 1 to 2 days WFH
🕐 Start: as soon as you are available
💼 Contract: full-time (CDI)
💰 Compensation: fixed salary + equity (BSPCE)
✅ Your missions
As Data Quality Specialist, you are the last line between a dataset and a frontier AI lab. Nothing ships without passing your bar.
You sit inside the tech team, embedded with the engineers who build the ingestion and anonymization pipeline, and you work every day alongside the Ops team who run the deliveries. You report to Grégoire (COO & co-founder).
This is a hands-on, individual contributor role. You own the quality function itself, not a team.
- Define the standard. Acceptance criteria, checklists, sampling methods, error thresholds. Today they barely exist. You write them, and you make them stick.
- Audit what we ship. Processed and anonymized data, reviewed before delivery: PII leakage, replacement consistency, structural integrity, and whether the business value survived the anonymization.
- Automate your own job. Manual review does not scale. You write the detection scripts and the analyses yourself, and you work with the engineers to turn the ones that prove themselves into production checks, so the obvious errors never reach a human again.
- Measure and escalate. Quality metrics per dataset and per vendor, including the third parties we work with. You track them, you surface the problems, and you drive them to resolution.
- Translate client requirements into specs. Work with the tech and sales teams to turn what a lab actually wants into concrete, testable quality criteria.
- Close the loop with engineering. You are the person who tells the pipeline team what is broken upstream, with the evidence to back it. Quality problems get fixed at the source, not patched at delivery.
🔍 Who we're looking for
- 4+ years in data quality, data operations, or QA, ideally at a data labeling company, a data provider, or an AI company.
- Hands-on with large, messy datasets: processing them, auditing them, finding what is wrong with them. Python and SQL are required: you write your own scripts to interrogate a dataset, you do not wait for someone to pull the data for you.
- Comfortable in a tech team. You will sit with engineers, read their pipeline, and hold your own in a technical conversation. You are not expected to ship production code, but you are expected to be credible.
- A track record of building quality standards from scratch, not just applying someone else's checklist.
- Obsessive attention to detail. You enjoy finding the error everyone else missed, and you are not satisfied until you understand why it was there.
- Systems thinking. When you find one error, your instinct is to ask how many others like it exist and how to catch them automatically.
- AI-first. You use LLMs and AI tools as daily leverage to audit, automate, and move faster.
- Fluent English, mandatory (working language with our partners and the labs).
The extras that make the difference
- Familiarity with PII, de-identification, or privacy requirements.
- Exposure to annotation quality concepts: rubrics, inter-annotator agreement, guideline design.
- Understanding of how training data is actually used: SFT, RLHF, RL environments, evaluation.
- Experience working with external vendors or an annotation workforce.
🎁 Why join us
- A function to build, not to inherit. Quality at Ooak Data is yours to define from the ground up.
- Your work is visible. What you validate goes straight to the largest AI labs in the world.
- Entrepreneurial adventure: founding impact, live the early days of an ambitious company at the front line of the AI revolution.
- Backed by Y Combinator, join just as we accelerate.
- Offices in central Paris.
- Perks: Alan health insurance (mutuelle), 50% Navigo covered.
###
About Ooak Data
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.
Other roles at Ooak Data
•
Head of Operations
Paris, ParisFull-time
•
Operations Manager - Data & AI
Paris, ParisFull-time
•
GTM AI labs (US)
San Francisco, CAFull-time
•
Account Executive - Data Partnerships (US)
San Francisco, CAFull-time
•
Head of Engineering
Paris, ParisFull-time
Interested?
Let me introduce you to the founders.
Skip the process
Job details
Salary
$65,000 - $80,000
Location
Paris, Paris
Experience
6+ years
Company
NameOoak Data
IndustryAI / Machine Learning
Team Size15
View profile
Funding
Last stage
Seed
Investors
Y Combinator
Founders
Pierre-Louis Vouteau
Co-Founder & CEO
Thomas Aubry
Co-Founder & CTO
GL
Grégoire L.
Co-Founder
What happens next.
No applications, no recruiter spam. Just the intro.
01
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
02
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
03
A meeting lands on your calendar
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.