AI Engineering Intern

Location: On-site in London

Company

hirify.global is building organic software for finance companies: systems that adapt to users and businesses, learn from usage, and improve their own behaviour.

What you will do

• Improve agents by analyzing merged pull requests and corrections, updating repository-specific instructions, and validating whether those changes improve performance.
• Fine-tune and deploy LLM and machine learning models, run experiments, compare results, and assess production readiness.
• Build end-to-end agents that support self-healing software pipelines, fix issues, and communicate with customers.
• Define evaluation criteria, build tests and review tools, and identify poor outputs before they reach customers.
• Own engineering projects from scoping and implementation through debugging, delivery, and production adoption.

Requirements

• Currently studying at the University of Oxford or the University of Cambridge.
• Silver medal or higher at the International Mathematical Olympiad or International Olympiad in Informatics, or an equivalent achievement in another highly competitive field.
• Strong programming ability and experience building something useful beyond coursework or tutorials.
• Hands-on experience with AI tooling, including LLM APIs, agent frameworks, model fine-tuning, or automated workflows.
• Ability to investigate system failures, test solutions, and clearly explain technical decisions.

Nice to have

• Open-source contributions.
• Experience deploying models.
• Experience building evaluation pipelines.

Culture & Benefits

• Internship compensation above the standard market rate.
• Ownership from the first day, with opportunities to ship work into production.
• Work alongside the product and engineering team in the London office.
• Success is measured through improvements in agent correctness, model accuracy, failure reduction, and continued use of shipped tools.

Hiring process

• Submit a CV and a link to something you have shipped.
• Explain what you built, your individual contribution, where it failed, how you fixed it, and why you want to work on organic software.