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.
⭐ Lead your CV with the AWS Certified Cloud Practitioner certification and any project completions (e.g. the RAG chatbot or sentiment analysis classifier), as these are the tangible outputs employers will look for from this programme.
📊 Quantify your project work wherever possible: "Built a car price prediction app in Streamlit achieving 87% model accuracy" or "Developed a RAG chatbot integrating a 10,000-document knowledge base".
🎯 Create a GitHub portfolio showcasing all programme projects (sentiment analysis, RAG chatbot, ML project) and link it prominently in your CV header — Kirklees-area tech employers will expect to see working code.
🌐 Highlight your Python progression explicitly: list libraries mastered (NumPy, Pandas, Matplotlib, scikit-learn) and note object-oriented programming competency, as these are ATS-critical keywords for junior AI roles.
🤝 In your personal statement, reference AI & Data Ethics training and prompt engineering skills — these are differentiators for candidates at entry level and signal awareness of responsible AI deployment.
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 RAG-powered customer service chatbot integrating a 5,000-document knowledge base using Hugging Face, LangChain, and a vector database, reducing simulated query resolution time by 40%.
- •Developed a car price prediction Streamlit application in Python achieving 85% model accuracy, applying NumPy, Pandas, and scikit-learn across a dataset of 12,000 vehicle records.
- •Completed AWS Certified Cloud Practitioner examination and 15-module AI engineering programme within 10 weeks, delivering 3 end-to-end AI projects assessed via 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 stood out immediately for its structured, project-led approach — covering Python, Retrieval-Augmented Generation, and AWS Cloud Practitioner certification in a single programme. These are precisely the skills I have been building to transition into AI engineering, and the job-guarantee model signals a seriousness about candidate outcomes that I find compelling.
My background in self-directed learning and problem-solving has prepared me well for the pace of this programme. Having worked through data fundamentals, prompt engineering principles, and hands-on projects including a sentiment analysis classifier built with Hugging Face and a RAG-powered customer service chatbot, I am confident in applying these skills to real-world AI challenges from day one.
Free signup, no card needed. Export to PDF/Word requires a £1.99 trial (14 days).
Interview questions
10 questions generated from this advert.
Technical
- ›Can you explain how Retrieval-Augmented Generation (RAG) works and describe a scenario where you would choose it over fine-tuning a language model?
- ›Walk me through the data preprocessing steps you would apply to a raw dataset before training a machine learning model using scikit-learn.
- ›What is the difference between a large language model and a traditional machine learning model, and when would you use each?
- ›How would you craft an effective prompt for a customer service chatbot to ensure consistent, accurate responses? Give a concrete example.
- ›What are vector databases, and how do they support AI applications such as semantic search or RAG pipelines?
Behavioural
- ›Tell me about a time you had to learn a completely new technical skill quickly — how did you approach it and what was the outcome?
- ›Describe a situation where you identified an ethical concern in a project or process. How did you handle it?
- ›Give an example of a self-directed project you completed without external deadlines. How did you stay motivated and on track?
- ›Tell me about a time you encountered a problem you couldn't immediately solve. What steps did you take to work through it?
- ›Describe a situation where you had to explain a technical concept to a non-technical person. How did you adapt your communication?
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 quickly — how did you approach it and what was the outcome?
Describe a situation where you identified an ethical concern in a project or process. How did you handle it?