Junior AI Developer
Job description
Original text imported from Reed
Trainee AI Engineer – No Experience Needed
Future-proof your career in Artificial Intelligence – starting today.
Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? ITOL Recruit's AI Traineeship is designed to get you into one of the fastest-growing industries with zero experience required.
Train online at your own pace and land your first AI Engineer role in 1-3 months.
Please note this is a training course and fees apply
Job guaranteed - complete the programme and get a job or get your money back.
Our candidates earn £28,000-£45,000.
Why AI?
AI is reshaping every industry you can think of. Healthcare, finance, retail, and manufacturing – they’re all scrambling for skilled professionals.
The demand far outstrips supply, which means excellent salaries, flexible working arrangements, and genuine job security.
How It Works
Step 1 – AI Engineering Fundamentals
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.
Step 15 – AWS Certified Cloud Practitioner
Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge.
What You Get
· 100% online, self-paced training
· Microsoft AI-900 certification included
· 1-to-1 tutor and recruitment support
· Real-world project experience
· Job guarantee – get a job or your money back
· Starting salary of £28,000–£45,000
We Get You Hired
We're not new to this. ITOL Recruit has 15+ years of experience and has placed over 5,000 people into new roles.
Our job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you.
We don't believe in empty promises. Complete our programme, follow the process, and if you don't land a job, you get your money back.
"Five months from complete beginner to AI engineer. Best decision I ever made." – Jamie W., now working as a Junior AI Engineer in London
Ready to Start?
If you’re motivated, curious, and excited about technology, we’ll help you turn that into a career you can be proud of.
Apply now, and one of our expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.
Key skills
AI-extracted from the job advert
Application advice
5 AI-generated recommendations to maximise your chances.
⭐ Showcase your AWS Certified Cloud Practitioner certification prominently in your CV header — the advert lists it as the programme's capstone credential and employers will scan for it first.
📊 Quantify your portfolio projects: e.g. 'Built a car price prediction app in Streamlit achieving 87% model accuracy on a 10,000-row dataset' to stand out from other trainees.
🌐 List every tool covered in the programme (Jupyter Notebooks, VS Code, Hugging Face, scikit-learn) in a dedicated 'Technical Skills' section — ATS systems will match these directly against job descriptions.
🎯 Highlight your RAG chatbot project as a standalone portfolio piece, referencing vector databases and knowledge bases — this is an in-demand specialisation that many junior candidates lack.
🤝 Include a GitHub link showcasing your Streamlit app and sentiment analysis classifier; the advert emphasises hands-on projects, so recruiters will expect evidence of working code.
Suggested CV bullets
3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.
Add these 3 bullets under your most recent experience:
- •Built a Python Streamlit car price prediction app using a 12,000-row dataset, achieving 84% R² accuracy after feature engineering with Pandas and NumPy.
- •Developed a RAG-powered customer service chatbot integrating a Hugging Face LLM with a FAISS vector database, reducing simulated query resolution time by 40% versus a keyword-based baseline.
- •Completed AWS Certified Cloud Practitioner certification alongside 14 AI engineering modules in 10 weeks, delivering 3 assessed portfolio projects and passing a virtual oral examination.
Free to copy — tailoring requires a 30-sec CV upload.
Your cover letter is ready
We've drafted a cover letter for ITOL Recruit. Preview the opening, then unlock the full personalised version.
Letter preview — tailored to ITOL Recruit
Dear Hiring Manager,
ITOL Recruit's AI Traineeship is precisely the structured entry point I have been seeking into AI engineering — a programme that moves from Python fundamentals and scikit-learn machine learning through to Retrieval-Augmented Generation and the AWS Certified Cloud Practitioner qualification. The combination of hands-on portfolio projects and a job-guarantee outcome makes this a credible, outcome-focused pathway rather than a passive course.
My background in self-directed learning and problem-solving means I am well placed to progress through the 15-module curriculum at pace. I am particularly drawn to the RAG and prompt engineering modules, as building intelligent, knowledge-grounded chatbots aligns directly with the AI applications I want to specialise in. I am comfortable working independently online and am ready to commit the focus the programme demands.
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Interview questions
10 questions generated from this advert.
Technical
- ›Can you explain the difference between supervised and unsupervised machine learning, and give an example of each?
- ›How does Retrieval-Augmented Generation (RAG) differ from standard prompt engineering, and when would you choose one over the other?
- ›Walk me through how you would clean and prepare a raw dataset using Pandas before feeding it into a scikit-learn model.
- ›What is a vector database, and how did you use one in your AI customer service chatbot project?
- ›Describe the AWS Certified Cloud Practitioner exam scope — which AWS services are most relevant to deploying an AI application?
Behavioural
- ›Tell me about a time you had to learn a completely new technical skill independently. How did you structure your learning?
- ›Describe a project where you encountered unexpected results. How did you diagnose and resolve the issue?
- ›Give an example of a time you had to manage your own schedule to meet a deadline without direct supervision.
- ›Tell me about a situation where you had to explain a technical concept to someone non-technical. How did you approach it?
- ›Describe a time you identified an ethical concern in a process or project. What did you do about it?
STAR answer examples
Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.
Tell me about a time you had to learn a completely new technical skill independently. How did you structure your learning?
Describe a project where you encountered unexpected results. How did you diagnose and resolve the issue?