Graduate AI Engineer

Southampton
1 week ago
Applications closed

Related Jobs

View all jobs

Graduate AI & Machine Learning Engineer...

Multimodal AI Researcher - PhD / Machine Learning / Python / C++

Principal Data Scientist - Remote

Machine Learning Consultant - Experienced

Graduate Business Development Executive

InTent Internship Programme 2025 (#IIP): Paid Summer Placement/Internship for Undergraduate’s (Bachelor’s) or Graduate’s (Master’s) Students in Agricultural Sciences, Environmental Sciences, Data Science (3months) at University of

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

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!