AI Engineer Intern - Real-World ML for Finance (6 Months)

Permutable; Greater London; Hybrid; GBP 18,000 - 24,000; Full time

Benefits offered by this job

Six-month internship

Job summary

Permutable AI in London is seeking a motivated AI Engineering Intern for a six-month placement hybrid. You will work with AI engineers, quantitative researchers and software developers on real-world financial applications, using LLMs, NLP pipelines and machine learning systems.

This hands-on role goes beyond theory: you'll contribute to production-ready code, datasets and AI tools used by institutional clients, with mentorship from experienced engineers, researchers and a path to practical

Qualifications

• Exceptional STEM background.
• Foundational understanding of machine learning, artificial intelligence or natural language processing.
• Understanding of APIs, data structures and software development principles.

Responsibilities

• Experiment with large language models (LLMs), including open-source and commercial models.
• Assist in building and testing multi-agent AI systems capable of researching, reasoning and analysing complex information.
• Develop and evaluate NLP pipelines for extracting entities, events, topics and sentiment from unstructured text.
• Help create automated workflows for processing and analysing large volumes of financial and economic information.
• Support the development of AI evaluation frameworks to measure accuracy, consistency, latency and reliability.
• Help integrate AI models into existing applications and APIs.

Skills

Foundational ML/AI/NLP knowledge

Familiarity with LLMs

API knowledge

Education

Recent graduate in Computer Science, Artificial Intelligence, Mathematics, Engineering, Data Science or related technical subject

Job description

Permutable AI in London is seeking a motivated AI Engineering Intern for a six-month placement hybrid. You will work with AI engineers, quantitative researchers and software developers on real-world financial applications, using LLMs, NLP pipelines and machine learning systems.

This hands-on role goes beyond theory: you'll contribute to production-ready code, datasets and AI tools used by institutional clients, with mentorship from experienced engineers, researchers and a path to practical