We're hiring exceptional AI researchers to shape the next generation of foundation models in Europe, both developing new AI models and architectures in-house and post‑training existing open‑source base models.

This is not a role focused only on applying existing models. You’ll work on both:

developing new model architectures in‑house in support of deterministic simulation, and
post‑training and adapting state‑of‑the‑art open‑source base models

Requirements

Strong research track record in machine learning, deep learning, or foundation models: evidenced by research publications, open‑source contributions, or other evidence of original technical work
Deep understanding of modern model architectures, training dynamics, inference optimization, scaling, and evaluation: transformer, diffusion, and exotic model architectures, sequence modeling, multimodal learning, and generative modeling
Hands‑on experience training, fine‑tuning, or post‑training large models: in particular preference optimization, synthetic data, distillation, continual learning, or alignment
Strong coding and experimental skills: ideally in Python (and/or Rust) and modern ML tooling
Ability to move fluidly between research ideas and practical implementation: comfort quickly moving from concept to early‑proof right through to release and productization
High agency, strong taste, and excitement about building something category‑defining from Europe: we’re looking for researchers who are all‑in

What you’ll work on

Research and develop novel model architectures for reasoning, representation learning, and world modeling
Post‑train and adapt open‑source foundation models for high‑performance real‑world use cases
Design, run, and analyze experiments across training, evaluation, and scaling
Work across data, systems, and product to turn research into deployed capability
Contribute to research direction, technical strategy, and long‑term model roadmap
Help define the culture and standards of a high‑talent, research‑driven founding team

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