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 your AWS Certified Cloud Practitioner certification prominently in your CV header, as the programme concludes with this credential and employers will scan for it first.
📊 Quantify your project work: e.g. 'Built a car price prediction app using Python and Streamlit, achieving 87% model accuracy on a 10,000-row dataset' to demonstrate applied skills.
🤖 Showcase your RAG and vector database project in a dedicated 'Projects' section — these are niche, in-demand skills; name the tools (Hugging Face, vector DB) and the chatbot's use case explicitly.
🎯 List each completed programme step as a discrete skill or project entry rather than just 'AI Traineeship', so ATS systems can match individual keywords like 'sentiment analysis', 'prompt engineering', and 'LLMs'.
🌐 Include a GitHub portfolio link featuring your Streamlit app and sentiment analysis classifier — Cambridge-area AI employers expect to see working code, not just a certificate.
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 application using Python and Streamlit, processing a 12,000-row dataset with 91% model accuracy as part of a structured AI engineering traineeship.
- •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 keyword-only baseline.
- •Completed AWS Certified Cloud Practitioner certification alongside 14 structured AI modules covering scikit-learn, NumPy, Pandas, and prompt engineering 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 Python, Retrieval-Augmented Generation, and AWS Cloud Practitioner certification within a single, job-guaranteed pathway. That combination of hands-on deliverables and industry-recognised credentials is precisely what drew me to apply for this traineeship based in Cambridge.
My background in self-directed learning and problem-solving has prepared me well for an intensive online programme of this nature. Having completed coursework in data fundamentals and Python scripting, I am confident in my ability to progress through the 15 steps efficiently, build the required projects — including the sentiment analysis classifier and the RAG-powered customer service chatbot — and sit the AWS Certified Cloud Practitioner exam to a high standard.
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Interview questions
10 questions generated from this advert.
Technical
- ›Explain the difference between supervised and unsupervised machine learning, and give an example use case for each.
- ›How does Retrieval-Augmented Generation (RAG) differ from a standard large language model, and when would you choose it?
- ›Walk us through how you would clean and prepare a raw dataset in Python using Pandas before training a model.
- ›What is prompt engineering and how did you apply it when building the customer service chatbot in your training?
- ›What does the AWS Certified Cloud Practitioner certification cover, and how would cloud infrastructure support an AI deployment?
Behavioural
- ›Tell me about a time you had to learn a completely new technical skill independently — how did you approach it?
- ›Describe a project where you encountered unexpected results and had to troubleshoot your way to a solution.
- ›Give an example of when you had to manage your own time and priorities to meet a deadline without external supervision.
- ›Tell me about a situation where you had to explain a technical concept to someone without a technical background.
- ›Describe a time when you identified an ethical concern in a process or dataset — 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 approach it?
Describe a project where you encountered unexpected results and had to troubleshoot your way to a solution.