1,726 to 1,750 of 5,363 Machine Learning Jobs in the UK

+ Bonus + Car Allowance This is an opportunity to join a highly data-driven organisation where pricing, analytics, and machine learning sit at the heart of business strategy. You will work on innovative data science initiatives that directly influence risk assessment, pricing decisions, and commercial performance, while … well-established consumer-focused organisation undergoing significant investment in data, analytics, and technology. With a strong emphasis on innovation, they use advanced machine learning and predictive modelling to support strategic decision-making and deliver better customer outcomes. Their analytics community brings together Data Scientists, Analysts, and Data Engineers ...

across teams (Product, Data Science, Investigations). Nice to Have Familiarity with the machine learning lifecycle (data pipelines, feature engineering, and deploying ML systems into production). Benefits Starting salary: £87,500 - £111,000 Wise Benefits Additional Information We’re people building money without borders — without judgement ...

Qualifications:1–3 years of professional experience writing clean, preferably in modern C++, with a strong grasp of memory management and multi-threading.AI/ML Familiarity: Academic or professional experience working with machine learning libraries and frameworks.Interest in trading and financial markets.Ability to work in a fast-paced ...

analytics function is seeking a Data Scientist to join its central Data & AI team. This is an opportunity to help shape the organisation's machine learning and predictive analytics capability, using large-scale operational datasets to deliver actionable insights that support better decision-making. Working closely with technical … business stakeholders, you will develop advanced analytical solutions that identify future risks, opportunities, and outcomes. Key Responsibilities Develop predictive and prescriptive models using machine learning and statistical techniques. Analyse large and complex datasets to identify patterns, trends, risks, and performance opportunities. Work with stakeholders to define business problems ...

created in the future.How you’ll make an impact: You’ll be the delivery backbone for a fast-moving, cross-functional engineering + ML team, making sure work is well-shaped, visible, and consistently shipped. You’ll bring disciplined agile execution (without heavy bureaucracy), so the team can run reliable … WIPrelease notes and sprint summaries in ConfluenceRAID tracking (risks, assumptions, issues, dependencies) with clear mitigation ownersCoordinate cross-functional delivery with Product, Engineering, DS/ML, Research Methodology, Security, and Privacy:ensure required reviews are built into the workflow (e.g., data governance checks, security approvals)manage external dependencies (data availability, platform ...

impact role where you'll help shape how AI is designed, built, and deployed across the organisation. You'll work at the intersection of machine learning, software engineering, and real-world business challenges-developing intelligent, scalable solutions that drive efficiency and innovation across our operations. Working closely with … engineering and audit standards Champion scalable, secure, and efficient AI implementation. What We're Looking For Core Skills & Experience Strong experience in AI Engineering, ML/LLM applications, or intelligent automation Solid Java engineering background with production-quality coding practices Experience with CI/CD tools e.g., Jenkins, GitLab ...

part of this growth, they're looking for a Senior Data Architect to design and deliver enterprise-scale data platforms that power advanced analytics, machine learning and AI solutions. This is an opportunity to work on large-scale transformation programmes, influencing data strategy and architecture while working with … platforms. Define data architecture strategies, standards and governance. Deliver modern data solutions using Databricks , Snowflake , AWS and GCP . Enable advanced analytics, AI and machine learning capabilities. Work closely with engineering, data and business teams to deliver end-to-end solutions. Provide technical leadership throughout the project lifecycle. ...

Developing, enhancing and productionising machine learning time-series forecasting models, with an initial focus on wind and solar generation. Building, automating and maintaining forecasting pipelines to ensure accurate, reliable and timely model outputs for traders. Collaborating with data engineering teams to onboard new data feeds, monitor data quality … while providing technical modelling support to analysts and key stakeholders. You will need to have the following: A PhD or equivalent advanced qualification in Machine Learning, Data Science, Statistics, Mathematics or another quantitative discipline. Experience building and deploying production-grade machine learning models, with a solid ...

without the right engineering layer, they never reach end users. That is where you come in. You will help build the “last mile” between machine learning and clinical application, turning models into reliable, scalable and usable products that support clinical trial teams in making better decisions. What … support and well-being)Remote or hybrid workingWhat You'll Be DoingBuild the integration layer for AI solutions Develop services and APIs that enable ML models to be deployed and consumed within the platform Translate data science outputs into production-ready components Full stack application development Implement frontend and backend ...

Retail, Python, SQL, Roadmaps, Cloud Analytics, Southampton area 2-3 days a month minimum. You will be leading a Data Science team to deliver machine learning and advanced analytics solutions that improve customer insight, drive commercial decision-making and enable personalisation across a retail organisation. You will … high-performing Data Science team. Own and deliver the Data Science roadmap, prioritising work based on business value. Oversee the development and deployment of machine learning models, including churn, customer lifetime value, forecasting, segmentation and recommendation. Ensure solutions are scalable, robust, governed and production-ready. Partner with business ...

cyber defence capabilities.This is a hands-on role suited to someone who understands modern security engineering and has a strong interest in AI/ML technologies, LLMs, automation, and risk management.What you’ll be responsible forDesign and implement security controls for AI and machine learning solutions, including … core security domains such as identity and access management, cloud security, application security, data protection, logging and monitoring, and incident response.Knowledge of AI/ML and LLM concepts, including model deployment patterns, APIs, embeddings, vector stores, prompt handling, and common AI security risks.Experience securing cloud environments and modern development workflows ...

drive the next generation of data-driven decision making across our products, platforms and customer experiences. This role combines advanced analytics, experimentation, machine learning, optimisation, and strategic leadership to solve complex business problems at scale. As a Principal Data Scientist, you will shape product strategy, influence executive decision … behaviour, product performance and business impact. Lead complex experimentation programs, including A/B testing, causal inference, uplift modelling and quasi-experimental methods. Develop machine learning, optimisation and decision science solutions that improve customer experience and operational efficiency. Translate ambiguous business challenges into structured analytical problems and actionable ...

design overall beneficial solutions to large scale AI infrastructure problems. You will build system models and architectural simulations to explore the design space, conduct ML-system co-design to align hardware capabilities with the demands of agentic AI and large-scale inference workloads, and contribute to software system prototypes that …/training infrastructure. Experience in building high-performance LLM inference systems using SGLang or vLLM. Publications in top computer architecture, systems, and/or ML conferences. Research Sciences IC4 - The typical base pay range for this role across United Kingdom is 74,700.00 - 122,600.00 per year. Certain roles ...

Engineer to build the application-level AI capability inside a large-scale AI adoption programme for a central government department. Where the Machine Learning Engineer trains models and the MLOps Engineer runs the platform, you sit closest to the end product: turning LLMs, retrieval systems, and agentic workflows … government or the wider public sector Familiarity with GOV.UK Service Standard expectations Exposure to open-source LLM tooling or communities Familiarity with AI/ML tooling on AWS, Azure, or GCP Location and Working Pattern Hybrid, based from Newcastle upon Tyne, with on-site attendance required for workshops, knowledge-transfer ...

centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful … developing innovative approaches to customer risk assessment and pricing. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models that improve pricing and customer selection strategies Exploring and evaluating new data sources to identify commercial opportunities Developing geospatial and footprint models ...

centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful … developing innovative approaches to customer risk assessment and pricing. Specifically, you can expect to be involved in the following: Building and deploying predictive machine learning models that improve pricing and customer selection strategies Exploring and evaluating new data sources to identify commercial opportunities Developing geospatial and footprint models ...

problems across the full-stack as we continue to push technology forward. Our team has a decade-long track record of successfully bringing ML ideas from theory to practice in the world of online ads. We have made it much easier for small and medium-sized content creators to grow … future apps.### Skills Required* Full Stack Development* Java* C++* Android* iOS* JavaScript* TypeScript* Software Testing* Software Maintenance* Software Launch* Software Design* Software Architecture* Machine Learning* Data Structures* Algorithms* Technical Leadership* Big Data* Information Retrieval* Distributed Computing* Large-scale System Design* Networking* Data Storage* Security* Artificial Intelligence* Natural Language ...

someone who enjoys technical depth, variety, and ownership, and who is comfortable applying the right techniques to each problem - from statistical analysis through to machine learning and deep learning models. You’ll join a small, high-calibre team that values autonomy, flexibility and technical excellence. The environment … actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. Working with large, structured and unstructured datasets, combining ...

hybrid cloud transformation solutions.Responsibilities: Design, architect and lead the delivery of AI-ready infrastructure platforms that enable large-scale machine learning (ML), generative AI (GenAI), agentic AI and high-performance computing (HPC) workloads.The successful candidate will be responsible for defining AI compute architectures across on-premises, colocation ...

move beyond experimentation and into real-world production environments. The Role As a Machine Learning Engineer, you will work across the full ML lifecycle, from designing and developing models through to deploying, scaling and continuously improving production systems. Depending on seniority, you will also have the opportunity … Develop and deploy production-grade Machine Learning solutions , building scalable AI systems that solve complex real-world challenges. Design end-to-end ML architectures , including model development, MLOps pipelines, deployment strategies and continuous optimisation. Collaborate with engineering, data and product teams to deliver robust, production-ready AI solutions ...

leading-edge technologies Foster a team culture of diversity, opportunity, inclusion, and respect Required Qualifications, Capabilities, and Skills Proficiency in Engineering & Architecture, AI/ML, with hands‐on experience designing, implementing, testing, and ensuring operational stability of large‐scale enterprise data platforms Advanced skills in one or more programming languages … PySpark and other big data processing technologies Demonstrated proficiency in software applications and technical processes within disciplines such as data engineering, cloud, artificial intelligence, machine learning, or mobile Knowledge of the financial services industry and their IT systems Equal Opportunity We are an equal opportunity employer and place ...

individuals who enjoy solving problems through automation, have experience integrating tools and workflows, and are curious about emerging technologies such as AI and machine learning . If you're passionate about modern cyber security, cloud technologies and building smarter, more efficient security solutions, this role offers the opportunity … threat hunting, investigations and continuous security improvement initiatives. Contribute to the secure adoption of AI-enabled technologies and identify opportunities to leverage automation and machine learning within security operations. Monitor emerging threats and help implement appropriate security controls and safeguards. Skills & Experience Essential Good level of experience within ...

develop agentic systems, ensuring AI agents operate within defined safety boundaries. Basic Qualifications PhD, or a Master's degree and experience in CS, CE, ML or related field research Experience in patents or publications at top-tier peer-reviewed conferences or journals Experience programming in Java, C++, Python or related … model checking tools and techniques, SAT/SMT solvers Knowledge of one or more methods of defining semantics: operational, denotational, axiomatic, etc. Experience applying machine learning and generative AI tools. Equal Opportunity Statement Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce ...

discoverable, well-governed, and AI-ready for machine learning, GenAI, and agentic use cases across the business. Partner with AI/ML teams to define patterns for feature engineering, model data pipelines, vector search, and safe exposure of enterprise data to AI systems. Evaluate emerging technologies and make ...

optimise recommendation systems (e.g. personalised product recommendations, ranking, search optimisation) Collaborate with data scientists, engineers, and product stakeholders to translate business requirements into ML solutions Implement and maintain MLOps pipelines to support continuous integration, delivery, and monitoring of models Ensure scalability, performance, and reliability of ML systems within Azure cloud … datasets to extract insights and improve model accuracy Monitor model performance and retrain models to maintain effectiveness over time Contribute to best practices in ML engineering, deployment, and governance YOUR KEY SKILLS: Strong experience as an ML Engineer in a production environment Proven expertise with Azure (e.g. Azure ML, Databricks ...