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Featured Jobs

Machine Learning Quant Engineer - Investment banking/ XVA

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. Inside IR35, 4 days a week on site The role: To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists at the forefront of...

Harvey Nash
London

Machine Learning Engineer

Machine Learning Engineer is sought by a high growth B2B scale up based in Birmingham city centre. With data-driven creativity at its core their platform uses machine learning to turn business insights into business success. As a Machine Learning Engineer, you'll sit at the intersection of data science, engineering, and commercial strategy, working closely with our product and core engineering...

SF Recruitment
Birmingham

Machine Learning Engineer (Databricks)

Machine Learning Engineer (Databricks) - £60 - £70k Edinburgh Hybrid - 2 days onsite I’m on the lookout for an MLOps Engineer who can truly bridge the gap between Data Engineering and Data Science. This role is all about leveraging Databricks and Python to design, build, and scale data models that drive genuine business impact. You’ll be joining a scaling...

Bright Purple
Roxburgh's Court

Machine Learning Engineer

Machine Learning Engineer | London (Hybrid) | £70,000 - £80,000 We are looking for a Machine Learning Engineer to join our London-based client, to deliver end-to-end solutions on exciting new projects which have come about due to growth. You’ll be designing, building and deploying machine learning models which solve complex business challenges, working closely with cross-functional teams at all stages,...

Peaple Talent
City of London

Machine Learning Engineer

Role: Machine Learning Engineer London: Central London - hybrid working Salary: £125,000 + bonus + benefits Industry: Technology Scale Up, circa 300 people The role: You will lead the design & development of robust Machine Learning models to solve complex problems. You will work alongside MLOps to help build the ML infrastructure for these models to be deployed, and then...

Arcus Search
City of London

Machine Learning Engineer

Machine Learning Engineer - 1 Month Initial Contract 📍 Location: Hybrid 1-2 days per week onsite in London 📅 Start: 24th November - 1 month initially but strong chance of extension 💰 Day Rate: Outside IR35 - rate depending on experience. An established consultancy is seeking a Machine Learning Engineer (Contract) to support a global education organisation on an ongoing...

Omnis Partners
London
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Career Advice

Advance your ML career with expert advice, practical job search tips, and insightful industry guides.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Jobs

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Jobs

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.

Education Careers

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Jobs

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

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