Graduate AI Engineer

Southampton
9 months ago
Applications closed

Related Jobs

View all jobs

Graduate Machine Learning and AI Engineer

Graduate Machine Learning and AI Engineer

Graduate Data Scientist - Cyber Analytics (Position located in Cheltenham, United Kingdom)

Junior / Graduate Data Scientist

Machine Learning Engineer Consultant

Graduate Data Scientist

Graduate AI Engineer - Tech for Good & Cutting-Edge ML

Location: Remote/Hybrid (UK or Ireland-based with occasional travel)
Contract: 9-month fixed-term (Full-time, PAYE)
Salary: Up to £49k for exceptional candidates

Make an Impact, Tech That Matters
Join a pioneering startup on a mission to break down digital barriers for the deaf community. This company is the first of its kind, using cutting-edge tech to translate digital and written content into sign language - making information truly accessible for everyone.

They're small, scrappy, ambitious, and working on a platform that combines AI, microservices, and cloud-native infrastructure to transform how sign language is delivered at scale.

Why Join?

Zero tech debt: Build from the ground up - clean slate.
Big purpose: Your work directly improves access to information for underserved communities.
Modern stack: Microservices, Python, FastAPI, React, Azure, AI/ML - all in play.
Ownership: Shape the architecture and engineering culture from day one.
Hybrid freedom: Mostly remote, with occasional travel to meet the team.What You'll Do

Design and develop ML models from scratch for NLP, computer vision, or generative AI
Collaborate with engineers and designers to ship end-to-end features
Work across the stack (Python, backend, and some frontend)
Learn how to deploy, monitor, and maintain production-grade ML services using MLOps principles
Help shape how tech is used to break down accessibility barriersAbout You

On track to graduate (or recently graduated) with a strong degree in AI, ML, or related field
You're curious, sharp, and motivated to learn quickly
Comfortable coding in Python and building ML models
Excited by real-world applications of ML, not just theory
Passionate about inclusive technology and ethical AI
Able to explain complex ideas simply, and work well in cross-functional teamsTech You'll Work With

ML & Data Science

Python (primary language)
TensorFlow, PyTorch, or Keras
NumPy, pandas
Data pipelines (Azure Data Factory, Airflow, etc.)
Applied ML: NLP, CV, transformers, GANs, time series, etc.Engineering & Cloud

Azure (or similar cloud platforms like AWS, GCP)
Microservices and event-driven architecture
Infrastructure as Code (Terraform, Bicep, Pulumi)
DevOps/MLOps: CI/CD workflows, monitoring (Grafana, Prometheus, Azure Monitor)
Bonus: Exposure to NVIDIA ML stack, cuDF/cuPy, AR/VR or neuromorphic computingWhat You'll Get

Competitive salary + potential for equity if hired full-time
Real ownership and influence in your work
Investment in professional development
A chance to make a measurable difference in people's liveThis is your chance to make a big impact early in your career. You'll be joining a tiny but mighty team building something genuinely innovative with AI and accessibility at its heart.

Want in? Hit reply, drop your CV, or even send a video - we're open to creative applications and encourage sign language users to apply too.

Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.