Trainee AI Engineer
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.
⭐ Highlight any self-directed learning or online courses at the top of your CV under a 'Professional Development' section, as this traineeship is fully self-paced and employers value proactive upskilling.
📊 Quantify your project outputs: e.g. 'Built a car price prediction app in Streamlit achieving 87% model accuracy using Python and Pandas within 4 weeks'.
🎯 Feature your AWS Certified Cloud Practitioner certification prominently — the advert lists it as the final and most employer-facing credential in the programme.
🤝 Reference the Hugging Face sentiment analysis and RAG chatbot projects by name in your CV's Projects section, as these demonstrate real-world AI engineering capability to hiring managers.
🌐 Tailor your CV summary to the Manchester tech market, noting readiness for roles across healthcare, finance, and retail AI applications as cited in the advert.
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:
- •Developed a car price prediction web application using Python and Streamlit, applying regression modelling techniques to a 10,000-row dataset with 82% prediction accuracy.
- •Built a RAG-powered customer service chatbot integrating Hugging Face LLMs and a vector database knowledge base, reducing simulated query resolution time by 40% versus a rule-based baseline.
- •Completed AWS Certified Cloud Practitioner certification alongside 14-module AI engineering curriculum, delivering 5 end-to-end projects within a 10-week self-paced programme.
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 Trainee AI Engineer programme stands out for its structured, project-led approach — covering prompt engineering, Retrieval-Augmented Generation, and AWS cloud certification within a single, outcome-focused traineeship. The job guarantee and hands-on curriculum, including building a sentiment analysis classifier with Hugging Face and a RAG-powered customer service chatbot, align precisely with the practical AI engineering skills I am committed to developing.
My background in self-directed learning and problem solving has prepared me to absorb technical content quickly and apply it to real-world challenges. I am confident that completing the 15-step programme — from Python fundamentals through to machine learning with scikit-learn — will equip me to contribute meaningfully to an employer from day one.
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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) work, and why would you use a vector database in an AI pipeline?
- ›Walk me through how you would clean and prepare a raw dataset for use in a machine learning model using Python.
- ›What is prompt engineering and how would you craft an effective prompt to control the output of a large language model?
- ›How does the AWS Certified Cloud Practitioner qualification relate to deploying AI applications in production environments?
Behavioural
- ›Tell me about a time you had to learn a completely new technical skill independently — how did you structure your learning?
- ›Describe a situation where you identified an ethical concern in a project or process. How did you handle it?
- ›Give an example of a time you built something from scratch with limited guidance. What was the outcome?
- ›Tell me about a time you had to manage your own time across multiple tasks or projects. How did you prioritise?
- ›Describe a moment when you received critical feedback on your work. How did you respond and what changed?
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 situation where you identified an ethical concern in a project or process. How did you handle it?