LEAD ML ENGINEER

Station F; Paris; Hybrid; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Alan health insurance (mutuelle)

Navigo covered 50%

Job summary

Station F is seeking a Lead ML Engineer in Paris to build and lead our ML team delivering anonymized data ecosystems for AI labs. You will own the ML pipeline, drive production-grade models, and collaborate with product teams.

You will prototype, code, and ship in production, mentoring engineers and shaping the roadmap for RL environments and model fine-tuning on company data.

Qualifications

• 8+ years in machine learning engineering, including 2+ years leading ML engineers.
• Deep hands-on expertise: Python, PyTorch or JAX with NLP and LLMs.
• Production ML at scale: shipped models to production and owned them: evaluation, monitoring, versioning, experiment tracking, GPU infrastructure.
• LLMs in practice: fine-tuning, inference and evaluation.
• AI-native way of building: you use coding agents every day and you know how to make a team ship faster with them.
• Research-literate: you read papers and turn them into things that ship.
• High bar on quality and security: we handle our partners' most sensitive data.
• Team first, low ego: you lead by clarity and trust, and you make the people around you better.
• Fluent English, mandatory (working language with our clients and the labs).

Responsibilities

• Own ML across the pipeline: detection of sensitive entities in text and images, entity resolution and the knowledge graph that keeps every pseudonym consistent across all tools, and document understanding to enrich our datasets.
• Automate quality: automated evaluation of anonymization and dataset quality, so delivery can scale without adding manual checks.
• Lead and grow the team: a few ML engineers today, around 6 by mid 2027. Priorities, 1:1s, hiring, and the technical bar.
• Stay hands-on: you prototype, code and ship to production yourself.
• Prepare what comes next with Thomas: RL environments and tasks built on our data, and fine-tuning open-source models on company data.
• Keep a close eye on research: read the papers, know where the frontier labs are heading, and turn it into our roadmap.

Skills

ML engineering

Team leadership

Python

NLP

LLMs

Production ML

Reinforcement learning

Knowledge graphs

Privacy-preserving ML

English fluent

Tools

PyTorch

JAX

GCP

GPU infrastructure

Job description

About

Our vision

The promise of AI agents is still unmet in complex, real-world business environments. Our mission is to make it possible for agents to reliably accomplish concrete and useful tasks.

That’s why we're building Alexandria, the world's largest library of real-world business workflow datasets.

Over the next 6 months, build our we'll acquire and anonymize 300+ full data ecosystems from real-world companies. This will allow us to become the leader of real business workflow data.

This summer we need to build our elite squad to move extremely fast and confirm our leading position on company data.

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.

We're building a solid, aligned, and motivated team.

Our traction speaks for itself: we've signed contracts with some of the largest AI labs in the world, alongside recent partnerships with several smaller labs, all while being 100% bootstrapped. This summer, we're joining Y Combinator, which is accelerating everything.

Job Description

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: €90k to €120k + bonus + equity (BSPCE).

Your missions

As Lead ML Engineer, you build and lead our ML team. You report to Thomas (CTO & co-founder).

Our ML team is central: it works with every product team on the hardest parts of the pipeline that turns full company data ecosystems into anonymized digital twins and training environments for the labs.

• Own ML across the pipeline: detection of sensitive entities in text and images, entity resolution and the knowledge graph that keeps every pseudonym consistent across all tools, and document understanding to enrich our datasets.
• Automate quality: automated evaluation of anonymization and dataset quality, so delivery can scale without adding manual checks.
• Lead and grow the team: a few ML engineers today, around 6 by mid 2027. Priorities, 1:1s, hiring, and the technical bar.
• Stay hands‑on: you prototype, code and ship to production yourself.
• Prepare what comes next with Thomas: RL environments and tasks built on our data, and fine‑tuning open‑source models on company data.
• Keep a close eye on research: read the papers, know where the frontier labs are heading, and turn it into our roadmap.

Your first months: you start embedded in one of our product teams for 1 to 3 months to learn the pipeline from the inside, then you take the lead of the ML team.

Why join us

• 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.

Preferred Experience

• 8+ years in machine learning engineering, including 2+ years leading ML engineers.
• Deep hands‑on expertise: Python, PyTorch or JAX with NLP and LLMs. Computer vision is a plus.
• Production ML at scale: you have shipped models to production and owned them: evaluation, monitoring, versioning, experiment tracking, GPU infrastructure (GCP or equivalent).
• LLMs in practice: fine‑tuning, inference (vLLM, SGLang or equivalent) and evaluation.
• AI‑native way of building: you use coding agents every day and you know how to make a team ship faster with them.
• Research‑literate: you read papers and turn them into things that ship.
• High bar on quality and security: we handle our partners' most sensitive data.
• Team first, low ego: you lead by clarity and trust, and you make the people around you better.
• Fluent English, mandatory (working language with our clients and the labs).

The extras that make the difference

• Experience with reinforcement learning: environments, reward design, RL frameworks.
• Experience with entity resolution or knowledge graphs.
• Experience with anonymization or privacy‑preserving ML.
• Experience at an AI lab.

Recruitment Process

• A 30 min intro call with Grégoire (co-founder)
• A 60 min technical deep dive with Thomas (CTO & co-founder): your track record, technical judgment, how you lead
• A technical ML case, presented to Thomas and an ML engineer
• A final fit interview with 2 founders
• Reference calls

Additional Information

• Contract Type: Full-Time
• Start Date: 04 January 2027
• Location: Paris
• Experience: > 7 years
• Occasional remote authorized
• Salary: between 90000€ and 120000€ / year