Trainee AI Engineer
Job description
Texte original importé depuis 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 extracted
Our AI analysed the job to identify the required skills.
Our tips for applying
5 recommandations générées par notre IA pour maximiser vos chances.
⭐ Lead your CV with the AWS Certified Cloud Practitioner credential and any Python projects completed during the traineeship — the advert lists these as programme endpoints and employers scan for them first.
📊 Quantify your portfolio projects: e.g. 'Built a RAG-powered customer service chatbot processing 500+ queries with 92% intent accuracy using Hugging Face and a vector database.'
🌐 Create a GitHub portfolio showcasing all three programme projects (car price prediction app, sentiment analysis classifier, customer service chatbot) and link it prominently in your CV header.
🎯 Mirror the advert's exact terminology in your skills section: 'Retrieval-Augmented Generation (RAG)', 'Large Language Models', and 'Prompt Engineering' are ATS-critical phrases for AI Engineer roles.
🤝 In your Personal Statement, reference the AI Ethics module (bias, fairness, data privacy) — this differentiates entry-level candidates and is increasingly required by regulated-sector employers in finance and healthcare.
Bullets CV suggérés
3 bullets générés par notre IA pour cette offre, alignés sur ses mots-clés ATS.
Ajoutez ces 3 bullets sous votre expérience la plus récente :
- •Built a RAG-powered customer service chatbot using Hugging Face, LangChain, and a vector database, achieving accurate intent resolution across 5 distinct query categories during the ITOL AI traineeship.
- •Developed a car price prediction Streamlit application in Python, applying OOP principles and Pandas data cleaning across a 10,000-row dataset to produce a model with under 8% mean absolute error.
- •Completed AWS Certified Cloud Practitioner certification alongside 14 structured AI engineering modules, delivering 3 end-to-end projects within a 3-month self-directed programme.
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Votre lettre de motivation est prête
Nous avons rédigé une lettre pour ITOL Recruit. Découvrez l'ouverture, puis débloquez la version complète personnalisée.
Aperçu — adapté à ITOL Recruit
Dear Hiring Manager,
ITOL Recruit's Trainee AI Engineer programme stands out precisely because it combines hands-on Python development and Retrieval-Augmented Generation techniques with a structured path to AWS Certified Cloud Practitioner — the combination that modern AI engineering roles demand. Having completed the 15-step curriculum, including building a RAG-powered customer service chatbot and a sentiment analysis classifier using Hugging Face, I am ready to contribute from day one.
My background in self-directed learning has equipped me with the discipline to work through complex technical material independently, and the three portfolio projects I completed during the programme demonstrate my ability to translate theory into working AI applications. I am comfortable with Python, NumPy, Pandas, scikit-learn, and prompt engineering, and I understand the ethical considerations around bias and data privacy that regulated-sector employers increasingly require.
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Likely interview questions
10 questions générées à partir de cette offre.
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 how you would clean and prepare a raw dataset using Pandas before feeding it into a scikit-learn model.
- ›What is the difference between supervised and unsupervised machine learning? Give an example use case for each.
- ›How does prompt engineering influence the output of a large language model, and what techniques did you use in your traineeship projects?
- ›What AWS services are relevant to deploying an AI application, and what does the Cloud Practitioner certification cover?
Behavioural
- ›Describe a time you had to learn a completely new technical skill independently — how did you structure your learning and measure your progress?
- ›Tell me about a project where you encountered unexpected data quality issues. How did you identify and resolve them?
- ›Give an example of a time you had to explain a technical concept to a non-technical person. How did you approach it?
- ›Describe a situation where you had to manage your time across multiple tasks without direct supervision. What was your approach?
- ›Tell me about a time you identified an ethical concern in a process or dataset. What did you do about it?
Exemples de réponses STAR
Réponses modèles avec la méthode Situation-Tâche-Action-Résultat. À adapter à votre vécu.
Describe a time you had to learn a completely new technical skill independently — how did you structure your learning and measure your progress?
Tell me about a project where you encountered unexpected data quality issues. How did you identify and resolve them?