AI Research Engineer

Location: In-office in London, UK or Berlin, Germany

Salary: £130,000–£220,000 base/bonus plus meaningful equity per year

Company

hirify.global builds open-source infrastructure that integrates structured and unstructured information into knowledge graphs for simulation, optimization, and automation.

What you will do

• 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 applications.
• Design, run, and analyze experiments across training, evaluation, and scaling.
• Work across data, systems, and product to turn research into deployed capabilities.
• Contribute to research direction, technical strategy, and the long-term model roadmap.
• Help define the culture and standards of a research-driven founding team.

Requirements

• Strong research track record in machine learning, deep learning, or foundation models, demonstrated through publications, open-source contributions, or original technical work.
• Deep understanding of modern model architectures, training dynamics, inference optimization, scaling, and evaluation, including transformers, diffusion, sequence modeling, multimodal learning, and generative modeling.
• Hands-on experience training, fine-tuning, or post-training large models, including preference optimization, synthetic data, distillation, continual learning, or alignment.
• Strong coding and experimental skills, ideally with Python and/or Rust and modern machine learning tooling.
• Ability to move from research concepts and early proofs through implementation, release, and productization.
• High agency and strong technical judgment, with enthusiasm for building advanced AI systems in Europe.

Culture & Benefits

• First-principles AI research connected to a significant real-world mission.
• Significant scope and influence within a rapidly growing organization.
• Open-source, research-driven environment with long-term focus.
• Leading equity-weighted total compensation with tax-advantaged options.
• Quarterly in-person whole-team retreats, generous learning and technology budgets, and output-based recognition.