ML engineer

We're ooak data

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
• be in the best position to launch our own data research lab in early 2027, enabling new services that help companies around the world automate their workflows with AI

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.

Your missions

As a Machine Learning Engineer and a founding member of the tech team, you'll play a central role in how we design, structure, and scale our products and our technical strategy. You'll report directly to Thomas (CTO & co-founder).

• Design, build, and scale our data ingestion, transformation, and structuring processes at scale.

• Contribute across every stage of our product:
  • the anonymization pipeline (combining algorithmic approaches with human verification) to build digital twin of companies.
  • the multi-modal data enrichment & curation pipeline
  • the reinforcement learning (RL) environments simulating real business contexts and workflows

• Define our technical standards, take an active part in the structuring architecture decisions (tech choices, design patterns, scalability, MLOps).

• Work closely with the product and business teams to scope and ship new data projects.

• Mentor and grow the future members of the tech team, building a strong ML engineering & software culture at Ooak Data.

Who we're looking for

• 5+ years of experience in Machine Learning Engineering or software development and data architecture.

• Strong coding experience using Python or Typescript and Rust

• Expertise in deep learning frameworks: PyTorch, JAX, or TensorFlow.

• Experience in Inference and RL framework: vLLM, SGLang, Slime

• MLOps & model deployment know-how: versioning, monitoring, experiment tracking.

• Proven track record delivering projects in an agile, collaborative environment.
• Genuine desire to mentor and grow more junior profiles over time.
• Demonstrated ability to thrive in a demanding, fast-growing environment.
• Excellent analytical skills, attention to detail, and strong prioritization.

• Fluent English, mandatory (working language with our clients and the labs).

The extras that make the difference

• Experience with GCP (or equivalent), Modal or GPU cluster and serverless technologies
• Experience with infrastructure as code (Terraform, CloudFormation).
• Strong interest in data anonymization, multi-modality, and RL environments.

Why join us

• Entrepreneurial adventure, play a key role and live the early days of an ambitious company, right at the front line of the AI revolution.

• Backed by Y Combinator, join just as we accelerate.

• Founding impact, shape the product, the tech stack, and the engineering culture from day one.

• Offices in central Paris + 1-2 days WFH.

• Perks:

  • Unlimited GPT & Claude tokens

  • Alan health insurance (mutuelle)

  • 50% Navigo covered

Recruitment process

We can move very fast.

• A 30-min intro call with Grégoire (COO & co-founder)
• A 30-min call with Thomas (CTO & co-founder)
• A technical case study:
  • Async preparation
  • Debrief interview with Thomas
• A final fit interview with the founding team
• Offer

• A 30-min intro call with Grégoire (COO & co-founder)

• A 30-min call with Thomas (CTO & co-founder)

• A technical case study:

  • Async preparation
  • Debrief interview with Thomas

• A final fit interview with the founding team

• Offer