Overview
Permanent, office-based AI Engineer role in London.
The Role
As an AI Engineer, you will be part of a core team driving the development of AI‑led solutions designed to improve productivity and efficiency across enterprise environments. This role offers the opportunity to work on cutting‑edge AI initiatives as organisations accelerate their adoption of artificial intelligence across industries. You will collaborate with experienced engineers and data scientists, leveraging modern AI, machine learning, and Generative AI technologies to build scalable, production‑ready solutions while continuously learning and experimenting with emerging tools and approaches.
Your Responsibilities
- Assist in designing, building, and maintaining scalable data pipelines for structured and unstructured data.
- Develop, train, and evaluate machine learning and deep learning models, including neural networks.
- Work with Large Language Models (LLMs) for tasks such as text generation, summarisation, and semantic analysis.
- Contribute to Generative AI (GenAI) use cases and experimentation.
- Implement and integrate RESTful APIs to deploy AI models into production environments.
- Collaborate with senior engineers and data scientists to improve model performance and reliability.
- Participate in code reviews, testing, and documentation to ensure high‑quality deliverables.
- Support model monitoring, debugging, and optimisation in real‑world applications.
- Stay up to date with emerging AI and ML trends, contributing innovative ideas to the team.
Your Profile
Essential skills/knowledge/experience:
- Proficiency in Python programming.
- Foundational understanding of machine learning concepts and algorithms.
- Familiarity with frameworks such as TensorFlow or PyTorch.
- Basic knowledge of Natural Language Processing (NLP) techniques.
- Understanding of neural networks and deep learning fundamentals.
- Exposure to Generative AI concepts and LLMs (e.g. prompt engineering, embeddings).
- Knowledge of working with APIs and data exchange formats (REST, JSON).
- Familiarity with version control systems such as Git.
- Strong analytical thinking and problem‑solving skills.
- Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, or a related field.
- Academic or project experience involving machine learning models, NLP, or AI systems.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Understanding of software engineering principles and the development lifecycle.
- Internship, coursework, or personal projects demonstrating applied AI/ML solutions.
- Strong communication skills and the ability to work effectively in a collaborative team environment.
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