Machine Learning Engineering ManagerLondonAbout the RoleAt Deliveroo we have an outstanding data science organisation, with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams - using analysis, experimentation, causal inference and machine learning techniques. We are uniquely placed to use data to help make better decisions...
Machine Learning Researcher - LLM/VLMAre you a PhD-educated Machine Learning Researcher looking for a new opportunity? If so, our client, a global consumer electronics company, is actively expanding their team. This role is based at one of their flagship AI centres in Cambridge, Cambridgeshire.Key Responsibilities:As a Machine Learning Researcher, you will:Work on on-device LLMs and VLMs, as well as adaptive...
Job Title: Machine Learning Engineer (real time Data Science Applications)Contract: 6 Months (possibility for extension)Location: London (2 days a week onsite)Rate: Circa £800/DayWorking Pattern: Full TimeJoin our client, a global leader in financial technology, as they empower businesses of all sizes to make, take, and manage payments seamlessly. With operations spanning 146 countries and 135 currencies, they are at the...
Job Title: Machine Learning Research ScientistLocation: Cambridge / HybridSalary: £depending on experience + benefitsCompany Overview: Our client is a pioneering machine learning and artificial intelligence software house, renowned for developing some of the most advanced technologies in the AI domain. The team is composed of mathematicians, engineers, and is led by experienced entrepreneurs known for creating award-winning tech companies.Job Description:...
Machine Learning EngineerDay Rate:Up to £650 outside IR35Industry:Defence/National SecurityLocation:CentralLondon - HybridDuration:3 Month RollingStart Date:1 Week NoticeThe Opportunity:The UK’s leading AI Consultancy seeks an influential ML Engineer to push the boundaries of innovation in a mission-critical defence project.The Role:You'll join a high-performing ML engineering team of data science and AI experts solving complex challenges in Radar and Sonar Signal Processing to...
Machine Learning Engineer | Research Platform:We are a tier 1 supplier for a well-known buy-side quant firm on the lookout for a Machine Learning Engineer (£475,000-£515,000) who is happy to work at the interface of cutting edge Machine Learning Modelling, Quantitative Research and HPC Systems Engineering.You will be a key player in developing core systems to support the training and...
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How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.
Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.
Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.
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