> Markdown version of [/jobs/ext/3019187-junior-ai-developer](https://www.wearedevelopers.com/jobs/ext/3019187-junior-ai-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Junior AI Developer - **Company:** ITonlinelearning - **Location:** Romford, UK - **Experience:** Starter - **Salary:** £28,000.0 - £45,000.0 - **Contract:** Temporary to permanent - **Skills:** Artificial Intelligence, Artificial Neural Networks, Python (Programming Language), Machine Learning, NumPy, Object-Oriented Software Development, Sentiment Analysis, Jupyter Notebook, Data Processing, Chatbots, Large Language Models, Prompt Engineering, Generative AI, Pandas, Matplotlib, HuggingFace, Streamlit Framework, Data Pipelines, Natural Language Generation - **Published:** September 21, 2026 - **Apply:** https://www.reed.co.uk/jobs/junior-ai-developer/57370659 ## About the Role If you're motivated, curious, and excited about technology, we'll help you turn that into a career you can be proud of. ## Description Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 - Data Fundamentals Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications. Step 3 - Notebooks & IDEs Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems. Step 4 - Python Programming Master Python, covering everything from the basics to object-oriented programming (OOP). Step 5 - Python Streamlit Project Apply your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning knowledge into practice with a hands-on project. Step 13 - AI & Data Ethics Study the ethical considerations in AI, including issues of bias, fairness, and data privacy. Step 14 - Oral Exam Complete a virtual oral exam to assess your understanding and ability to apply your learning., "Five months from complete beginner to AI engineer. Best decision I ever made." - Jamie W., now working as a Junior AI Engineer in London