Lead ML Engineer

present of AI; Paris; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

Ooak Data seeks a hands-on ML lead to own the end-to-end ML pipeline, from data preparation to anonymized twins and training environments. You will lead a small team of engineers, define priorities, and set the technical bar while continuing to code and ship personally.

You will gain hands-on experience with fine tuning, inference serving, and evaluation of large language models, plus exposure to RL environments, knowledge graphs, and privacy-preserving methods for sensitive data.

Qualifications

• Proven hands-on experience in Python with modern ML frameworks.
• Strong track record shipping models to production and owning end-to-end ML pipelines.
• Experience leading small engineering teams and setting technical bar.

Responsibilities

• Own ML across the pipeline from data to anonymized twins and training environments.
• Lead a small team of engineers, setting priorities and the technical bar.
• Code and ship personally while mentoring others and maintaining delivery cadence.
• Shape data, tasks, and evaluation criteria used to train models.

Skills

Python (PyTorch/JAX)

LLM fine-tuning & serving

Entity resolution & graphs

Leadership / people mgmt

Production ML / shipping models

Reinforcement learning environments

Privacy preserving methods

Tools

PyTorch

JAX

Job description

This role owns machine learning across a pipeline that turns raw company data into anonymized twins and training environments. A strong candidate brings deep hands on work in Python with PyTorch or JAX, natural language and large language model experience, and a record of shipping and owning models in production. It also calls for leading a small team of engineers, setting priorities and the technical bar, while still coding and shipping personally.

How it fits the AI era

The work sits close to how AI agents are trained, so the role shapes the data and tasks that models learn from. Much of the routine checking of data quality is meant to be automated, which shifts human effort toward judgment, design and oversight. What stays human is leading people, setting the technical bar, reading research and deciding what to build next.

How it builds AI experience

A person here would gain hands on practice with fine tuning, inference serving and evaluation of large language models, plus exposure to reinforcement learning environments and reward design. They would also build skill in entity resolution, knowledge graphs and privacy preserving methods for sensitive data. Using coding agents daily and helping a team ship faster with them is part of the expected way of working.

Worth showing

• Python with PyTorch or JAX
• LLM fine tuning and serving
• Entity resolution and graphs

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Ooak Data

Ooak Data builds reinforcement learning environments from real company data so AI agents can be trained and evaluated on expert-level tasks, per the company.