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⚡ Source: ReedRef: 56916609

Trainee AI Engineer

ITOL Recruit·Birmingham, West Midlands·Posted 1 week ago
💰 £30-45k/year
Tailor my CV for this job — Free

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.


SpeedCV AI

Key skills

AI-extracted from the job advert

Must-have skills
Python programmingJupyter NotebooksVS CodeNumPy and Pandasscikit-learnAWS Certified Cloud Practitioner
Nice-to-have
Hugging Face model integrationStreamlit application developmentVector database integrationPrompt Engineering
Soft skills
Self-motivationAutonomyAdaptabilityProblem solvingAttention to detail
SpeedCV AI

Application advice

5 AI-generated recommendations to maximise your chances.

1

⭐ Highlight any self-directed learning or online courses at the top of your CV under a 'Professional Development' section, as this traineeship is entirely self-paced and employers will want to see evidence of initiative.

2

📊 Quantify your project outcomes: e.g. 'Built a car price prediction app in Streamlit achieving 87% model accuracy using Python and Pandas across a 10,000-row dataset'.

3

🎯 Feature your AWS Certified Cloud Practitioner certification prominently in a dedicated 'Certifications' section — this is a named, verifiable credential that ATS systems will scan for.

4

🌐 List each portfolio project (sentiment analysis classifier, RAG chatbot, ML project) as a separate entry with a GitHub link, as hiring managers for AI roles expect tangible code artefacts.

5

🤝 Reference AI ethics knowledge explicitly in your personal statement, as the advert dedicates a full module to bias, fairness and data privacy — a differentiator few junior candidates mention.

NEW
AI SpeedCV

Suggested CV bullets

3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.

How to tailor your CV

Add these 3 bullets under your most recent experience:

  • Built a Python and Streamlit car price prediction application, applying OOP principles and Pandas data preprocessing across a structured 10,000-row dataset as part of a 15-module AI engineering curriculum.
  • Developed a Hugging Face sentiment analysis classifier using real-world NLP techniques, achieving end-to-end model deployment within a 3-month self-paced training programme.
  • Designed and deployed a RAG-powered customer service chatbot integrating vector databases and prompt engineering, reducing simulated query resolution time by 40% compared to a baseline keyword-matching approach.

Free to copy — tailoring requires a 30-sec CV upload.

NEW
AI cover letter

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 pathway I have been seeking to transition into AI engineering. The programme's breadth — from Python and scikit-learn through to Retrieval-Augmented Generation and the AWS Certified Cloud Practitioner qualification — aligns directly with the skills employers are actively recruiting for across healthcare, finance, and retail sectors.

My background in self-directed learning and project delivery means I am well placed to complete the 15-module curriculum at pace. I am particularly drawn to the hands-on project work, including the sentiment analysis classifier built with Hugging Face and the RAG-powered customer service chatbot, as these represent the kind of tangible portfolio artefacts that demonstrate real-world capability to hiring managers.

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Free signup, no card needed. Export to PDF/Word requires a £1.99 trial (14 days).

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SpeedCV AI

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 a standard large language model response, and when would you choose to use it?
  • Walk me through how you would preprocess a raw dataset using Pandas before feeding it into a scikit-learn model.
  • What is prompt engineering, and how would you craft a prompt to reduce hallucinations in an LLM-powered customer service chatbot?
  • Explain what a vector database is and how it is used in an AI application you have built or studied.

Behavioural

  • Tell me about a time you taught yourself a new technical skill independently — how did you structure your learning?
  • Describe a situation where you had to manage your time across multiple self-directed tasks without a manager setting deadlines.
  • Give an example of a project where something did not go to plan. How did you identify the problem and what did you do to resolve it?
  • Tell me about a time you had to explain a technical concept to someone without a technical background.
  • Describe a situation where you identified an ethical concern in a process or decision. How did you raise it and what was the outcome?
SpeedCV AINEW

STAR answer examples

Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.

1Question

Tell me about a time you taught yourself a new technical skill independently — how did you structure your learning?

Situation: I wanted to move into data analysis but had no formal training and was working full-time in a customer service role. Task: I needed to build enough Python proficiency to complete a take-home assessment for a junior analyst position within 6 weeks. Action: I blocked 90 minutes each morning before work, used a structured online curriculum covering NumPy and Pandas, and built a small project analysing 3 months of my own household spending data to apply each concept immediately. Result: I completed the assessment, was shortlisted from 47 applicants, and was offered the role. The hiring manager specifically noted the personal finance project as evidence of initiative.
2Question

Describe a situation where you had to manage your time across multiple self-directed tasks without a manager setting deadlines.

Situation: During a career break, I enrolled in two concurrent online courses — one covering SQL and one covering Python — while also volunteering 12 hours a week at a local charity. Task: I had to deliver a final project for each course within the same 4-week window with no external accountability. Action: I created a weekly sprint plan, allocating Monday and Wednesday evenings to Python and Tuesday and Thursday to SQL, and set personal milestones every 7 days. I reviewed progress each Sunday and adjusted the plan when the Python Streamlit project took longer than expected. Result: I submitted both projects on time, received a distinction on the SQL assessment, and the Python project was featured as a course example by the instructor.

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