1 to 25 of 1,186 Machine Learning Jobs in the UK

Machine Learning Engineer Join the analytics team as a Machine Learning Engineer in the insurance industry, where you'll design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward-thinking … environment. Client Details Machine Learning Engineer This opportunity is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients. Description Machine Learning Engineer Design ...

Machine Learning Engineer Join the analytics team as a Machine Learning Engineer in the insurance industry, where you'll design and implement innovative machine learning solutions. This permanent role in London offers an exciting opportunity to work on impactful projects in a forward-thinking … environment. Client Details Machine Learning Engineer This opportunity is with a medium-sized organisation in the insurance industry. The company is committed to utilising advanced analytics and machine learning to enhance its services and deliver value to its clients. Description Machine Learning Engineer Design ...

guide and influence the product direction and improve the customer experience. We are seeking a Senior Machine Learning Engineer to help pioneer ML innovation across Sonos' product and software ecosystem. This role will drive the design, development, and deployment of ML models that power data-driven decision-making … experimentation systems and customer segmentation models to predictive marketing and proactive self-help experiences. As a senior contributor, you'll lead end-to-end ML initiatives, mentor junior engineers, and collaborate cross-functionally with Data Analysts, Data Engineers, and business teams in Software, Product, Marketing, and CX. What ...

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have … within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity ...

Machine Learning Operations Engineer Our financial services client based in London is looking to recruit a Machine Learning Operations Engineer ASAP. The position will be a Hybrid role be working from home and their offices in London. To be considered for the role you must have … within the company. Technical Skills required Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity ...

develop, and deploy machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love … perfect opportunity to kickstart your career. What You’ll Be Doing You’ll play a key role in helping our team develop and deliver ML-powered solutions: Model Development : Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow ...

Overview We are seeking Senior Machine Learning Researcher candidates for our research in the area of People-Centric AI at Microsoft Research Cambridge (UK). The successful candidate will be responsible for pushing the state of the art in machine learning to enable human agency … mentoring junior researchers. Preferred Demonstrable ability to define an ambitious, original research agenda based on deep sociotechnical thinking, including the ability to formulate ML research questions from complex sociotechnical problem spaces. Experience working in a multidisciplinary team, including the ability to clearly translate technical concepts, ideas, and requirements ...

where you’ll not only design and build advanced machine learning solutions but also line-manage engineers, coordinate delivery across high-impact ML projects, and define the technical bar across the team. Your compensation reflects both the strategic leadership scope and technical excellence expected in this role. What … technical direction for GenAI and retrieval-based systems, ensuring consistent architecture, tooling, and research-to-production workflows. Act as delivery owner across multiple ML streams, coordinating timelines, resources, and cross-functional collaboration. Drive best practices for scalable, reproducible, and robust ML system development. Be hands-on when needed, contributing ...

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

techniques. We are uniquely placed to use data to help make better decisions and improve data literacy across Deliveroo. Machine Learning (ML) Engineers work in cross-functional teams of engineers, data scientists, and product managers to build the algorithmic products that power the company. We are embedded … product teams, close to the business problems and go after some of the hardest problems. ML Engineers translate a fuzzy business problem to a concrete pipeline that we design and implement. We then work closely with the engineers to deploy our models to production and with data scientists ...

leadership role: you’ll set the AI strategy, design and scale production NLP and machine learning systems, and grow a high-performing ML team - while closely partnering with Product and Engineering to deliver real, measurable impact for customers. This Head of AI & Machine Learning will Take … ownership of the company’s AI roadmap — from concept to production. Build and scale NLP and ML models that turn complex organisational data into meaningful insights. Lead and develop a small ML engineering team, acting as a player-coach. Establish MLOps, monitoring, governance, and responsible AI practices. Work cross-functionally ...

Head of AI The role At Rightmove, you’ll join a close-knit, collaborative AI team that’s developing, shipping and operating live ML/AI services that help Rightmove deliver exceptional experiences and value to consumers, our partners and all our stakeholders across the UK property market. … learning systems that leverage Rightmove’s data at large scale. You’ll have the opportunity to shape best practices, own and grow the ML Ops discipline, and help us move from first launches to robust, sustainable production. In this role, you will work in a cross-functional team ...

Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability of our AI tools. Implementing automation and standardization throughout the ML lifecycle, your efforts will support quicker, data-informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions … learning and large language models (LLMs) in practical operational settings, transforming research findings into functional business tools. Facilitate the progress and examination of ML models, involving both standard machine learning and neural network-focused models, as requested by R&D teams. Develop standardized, reusable workflows that ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A/B tests and offline … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton ...

personalization. In this role specifically, the Principal Data Scientist (Deep Learning) will lead algorithmic solution design, rapid prototyping, and technical review for the ML/AI models underlying personalized user experiences and content promotion. They will be a key point of contact for cross-functional architects and software developers … particularly for real-time and near real-time models. Desired Characteristics: Experience in content streaming or commerce as a senior contributor to AI/ML-powered product features and user experiences. Experience with reinforcement learning based systems. Experience with large-scale video assets. Ability to build trust across ...

intersection of data science, engineering, and commercial strategy, working closely with our product and core engineering teams to translate business challenges into deployable ML solutions. You'll have the autonomy to experiment, iterate, and bring ideas to production that directly impact revenue and user engagement. This role would suit … Machine Learning Engineer with at least three years commercial ML/AI experience gained working In a mission focussed, product led business. In return this ML Engineer will receive extensive growth and personal development opportunities as the business transitions away from legacy engineering practices. This ML Engineer based ...

just analyse data; you'll answer the critical questions that drive our strategy. We're looking for someone to use advanced data science and machine learning to uncover the 'why' behind customer behaviour, such as identifying complex churn triggers for our energy customers. You will also develop … Acquisition Cost (CAC). This isn't a research role. We need a "full-stack" data scientist who can own the end-to-end ML lifecycle. You will take your ideas from initial Proof of Concept (POC) and exploratory analysis all the way through to building, deploying, and maintaining production ...

metal components are conceived, tested, and produced - enabling breakthroughs in aerospace, energy, and beyond. This is a rare chance to apply your ML expertise to problems that have a tangible, physical impact - from inventing new alloys to optimising complex manufacturing processes. You'll collaborate with leading data scientists, engineers … materials researchers to build models that drive real-world innovation. Expect to design, validate, and deploy state-of-the-art ML pipelines that move seamlessly from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you'll fit right in. ...

cross-functional delivery teams working on technically complex, high-impact AI projects. You’ll play a central role in designing and building the ML architecture (from infrastructure and deployment to tooling and automation) to ensure that solutions are not only technically sound, but also scalable, maintainable, and secure. This … design and build of production-ready machine learning pipelines and systems Develop infrastructure and tooling to enable deployment, monitoring, and retraining of ML models Work across the full AI delivery lifecycle, from architecture and integration to performance optimisation Collaborate with customers and stakeholders to understand operational constraints ...

recruiting on behalf of a leading client in the technology sector who is seeking a highly skilled and experienced Machine Learning Engineer with a strong background in Reinforcement Learning. This role will contribute to the continued development of Arena, the company's web-based platform for reinforcement learning … algorithms and concepts, with practical experience in building and training reinforcement learning models. Excellent programming skills, with experience using reinforcement learning and ML frameworks (e.g. PyTorch, TensorFlow, Ray, Gym, RLLib, SB3, TRL) and MLOps tools. Solid understanding of hyperparameter optimisation techniques and strategies. Experience building machine learning ...

Senior ML Quant Engineer - Fixed Income - Artificial Intelligence Location London Business Area Engineering and CTO Ref # 10045475 Description & Requirements Bloomberg's Engineering AI department has 350+ AI practitioners building highly sought after products and features that shape global markets. In our fast-paced Fixed Income domain, you'll design … implement advanced models that leverage modern ML and statistical techniques on top of novel technology stacks and vast data sources to accurately price millions of securities. We are heavily invested in data-driven solutions that combine statistical and machine learning solutions to price diverse asset classes, with ...

established data function, working on real production workloads rather than prototypes. You'll play a key role in shaping how intelligent automation, LLMs and ML-driven services are designed, deployed and continuously improved. What you'll be working on * Designing and delivering Gen AI and LLM-driven applications* Building … maintaining machine learning pipelines and data workflows* Developing cloud-native (serverless) ML components within a distributed engineering team* Improving existing ML systems and identifying opportunities for optimisation* Supporting sprint planning, estimation and shaping a healthy product backlog What you'll need to bring * Strong hands-on Python skills ...

processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering … workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks, and implementing ...

Machine Learning Lead, youll be a hands-on Machine Learning Engineer with a strong track record of building and deploying ML solutions at scaleparticularly in NLP and GenAI. You will: Design, develop and scale NLP and GenAI capabilities to optimise business processes. Build out a robust … GenAI application technology stack, from experimentation through to production. Develop, maintain and improve existing ML pipelines, data transformation workflows and MLOps practices. Create serverless data/ML pipelines in cloud environments (Azure preferred). Work closely with architects, senior developers, product owners and business analysts to shape requirements, solution design ...

with prompt engineering, RAG architectures, and multimodal models. Contribute to internal tools for monitoring, testing, and improving AI performance. Stay on the edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience … environment. Is curious, ambitious, and eager to build real AI systems that have an impact. What You’ll Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, Hugging Face, OpenAI ...