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We are looking for an excellent ML Ops Engineer to join our research and development team. Key Responsibilities This opportunity is to join the ML Operations teams which supports the ML Development team in building leading-edge motion capture products through provisioning and maintaining a modern ML Operations stack. This stack covers data acquisition pipelines, data management and ML model training...
Job title: Machine Learning Engineer Locations: Manchester or Haywards Heath (hybrid working) Role overview Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment....
Ready to take your ML skills from experiment to impact? Are you a Machine Learning Engineer who’s passionate about building real-world solutions that make a difference, not just proof-of-concept models gathering dust? You’ll be at the core of our machine learning operations, designing and deploying scalable pipelines, owning our Azure ML platform, and collaborating with data scientists and analysts to...
We are looking for an excellent Computer Vision MLE to join our UK research and development team. Key Responsibilities This opportunity is to contribute to a team which is building leading-edge products with a particular focus on research innovation. You will have opportunities to contribute to technical direction, suggest new areas of research and the potential to guide your own...
Machine Learning Engineer (SC Cleared) London (Hybrid) 2 Month Contract £550/day (Inside IR35) Machine Learning Engineer needed with active SC Security Clearance, plus strong Databricks, MLFlow and MLOps experience. The ideal candidate will have a strong background in Machine Learning (ML) Engineering and in-depth expertise in operationalising models in Databricks, MLFlow and MLOps environments. A chance to work with a...
We are looking for an engineer with experience in low-level systems programming and optimisation to join our growing ML team. is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Your part here is optimising the performance of...
Advance your ML career with expert advice, practical job search tips, and insightful industry guides.
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.
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.
Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.
The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.
Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.
The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.
