Company
Join a fast-growing B2B technology company developing an AI-powered platform used by large enterprise customers. The product combines complex business data, machine learning, large language models, and AI agents to help organisations make faster, more informed decisions.
The business has established teams across Europe and the United States and is continuing to invest heavily in its AI and research capabilities. Its technology is already used in complex enterprise environments, with research teams working closely with engineering and product to turn advances in AI into measurable improvements for customers.
Role
As an AI Research Engineer, you will join a small, highly technical research team working on advanced AI projects that directly shape the product. You will combine rigorous research with practical engineering, focusing on large language models, AI agents, model fine-tuning, and wider machine learning systems.
- Design and run reproducible experiments involving large language models, AI agents, fine-tuning, and other machine learning systems.
- Investigate model convergence issues, inconsistent outputs, and unreliable behaviour across different architectures.
- Develop clean, modular, well-documented code and robust end-to-end research pipelines.
- Select appropriate frameworks and tools for rapid prototyping and production-ready development.
- Define research priorities based on their potential product and business impact.
- Turn research findings into practical improvements for data science, machine learning engineering, and product teams.
- Use MLOps and containerization practices to support reliable deployment into production.
- Communicate technical findings clearly to both specialist and non-technical audiences.
- Mentor colleagues, delegate work effectively, and help engineering teams adopt valuable research advances.
- Build relationships with universities and support the publication of high-quality research at leading AI conferences.
Key Skills
- Deep understanding of machine learning fundamentals, including classical machine learning, deep learning, model training, and model failure modes.
- Extensive, advanced experience with Python and SQL.
- Strong practical experience with large language models and AI agent workflows.
- Deep expertise in model fine-tuning and experimental evaluation.
- Ability to debug complex algorithms and diagnose unreliable or inconsistent model behaviour.
- Strong software engineering skills, including modular design, documentation, version control, and reproducible code and data pipelines.
- Experience taking machine learning solutions into production using Docker or similar container technologies.
- Advanced understanding of MLOps and end-to-end machine learning pipelines.
- Ability to work autonomously, set priorities, and solve complex problems in ambiguous environments.
- Clear communication and presentation skills for technical and non-technical stakeholders.
- Experience mentoring team members and providing technical or research leadership.
Desirable:
- PhD in a relevant technical field.
- Previous experience in an academic or industrial AI research laboratory.
- Published research in leading AI or machine learning conferences or journals.
- Experience with knowledge graphs.
- Experience developing university or academic research partnerships.
Benefits
- Opportunity to work on advanced AI research with a direct route into a real enterprise product.
- High levels of autonomy and end-to-end ownership of strategically important projects.
- Scope to influence research direction, product development, and engineering practices.
- Support to publish novel, high-quality findings at leading AI conferences.
Next Steps
If interested, please apply below or reach out directly [email protected]