1 to 25 of 1,609 Machine Learning Jobs in the UK

processes giving Markerstudy a critical advantage in the increasingly competitive insurance market by minimizing the development to deployment and monitoring stages of the ML lifecycle through automation. You will also be responsible for refining, tuning, deploying and maintaining machine learning methods in our machine learning pipeline … customer-centric offerings across Motor, Home and Commercial Lines businesses. The successful candidate will also enjoy opportunities for leading, coaching, and mentoring more junior ML Engineers. Key Responsibilities: Report and communicate with Senior Stakeholders, such as the Head of Data Science and Machine Learning and Director of Technical ...

services and deliver value to its clients. Description Machine Learning Engineer - London This role focuses on training custom models, building robust ML pipelines, and deploying systems at scale from research experimentation through to monitored production services. Design, train, and optimise machine learning models for audio processing … tasks such as speaker diarization, automatic speech recognition (ASR), and voice activity detection. Build and maintain training and inference pipelines using PyTorch, and related ML frameworks Source, curate, and prepare training datasets; implement preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results ...

ROLE OVERVIEW: We are currently looking for a Machine Learning Engineer to join a leading research organisation based in London. As Machine Learning Engineer, you will be responsible for advancing data-processing, model-building, and deployment capabilities for a pioneering research organisation. KEY DUTIES AND RESPONSIBILITIES … Your duties as the Machine Learning Engineer will be varied; however, the key duties and responsibilities are as follows: 1. Develop deep-learning pipelines for nuclear magnetic resonance (NMR) data and innovative machine learning approaches to elucidate and quantify interactions between small molecules and intrinsically ...

+ Bonuses & Benefits Location: Cheltenham (3 days on-site per week) Security Clearance: Active Enhanced DV (West) Required Key Skills: Machine Learning, AWS/Azure, Python, NLP, AI Who We Are? We are seeking a highly skilled Data Scientist with enhanced DV clearance to join a globally recognised … techniques to solve complex challenges Conducting research and innovation to develop cutting-edge solutions Keeping up to date with the latest developments in ML and data technologies Engaging in the full data science lifecycle, from data collection to model deployment Producing clear and well-documented technical outputs Delivering high ...

Learning Engineering within a large, established organisation that is genuinely investing in data and AI. This role offers the chance to lead ML engineering capability, productionise high-impact use cases, and shape how machine learning is delivered at scale across the business. The Company They … architecture to support scalable analytics and machine learning. The Role As Lead Machine Learning Engineer, you will take technical ownership of ML engineering and play a key role in building out the wider capability. Key responsibilities include: Leading the design and delivery of end-to-end machine ...

work is thoughtful, challenging, and purposeful, rather than driven by novelty or trend. What you'll be doing You'll take ownership of complex ML problems, applying scientific thinking and pragmatism in equal measure. You will: Lead end-to-end machine learning delivery , from problem definition through experimentation … with internal teams and selected external partners working at the leading edge of AI What we're looking for This role suits a senior ML practitioner who values judgement, evidence, and outcomes over theoretical or tooling purity. Essential experience: Proven experience operating at senior practitioner level as a Machine ...

learning solutions, helping organisations turn complex data into intelligent, real-world outcomes. What you'll have the opportunity to do as a Data & ML Engineer Building and maintaining scalable data pipelines that support analytics and machine learning Developing and deploying machine learning models into production … Supporting good engineering practice across testing, automation and deployment Contributing to Agile delivery through teamwork and continuous improvement About the Candidate The right Data & ML Engineer should have: Experience in data engineering, machine learning or applied AI roles Strong skills in Python and SQL, with exposure ...

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 ...

very excited about our plans for growth over the coming year and beyond! The role We are now looking for a Machine Learning Engineer to build and deliver innovative AI products to our customers. Your software expertise and machine learning knowledge will help transform our customers … challenges and collaborate with them to leverage our AI in the automation of their work. Initially, you will provide hands-on support for our machine learning models as they come to market but then will gradually develop self-service tools that empower customers to achieve value independently. ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature … Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring, Maintenance, and Continuous Learning; Data Security, Privacy, and Governance; Stakeholder Communication and Documentation The Multiverse coaching team is a diverse mix of industry experts, educators, and academics ...

deploy machine learning models and pipelines in production environments Collaborate with data scientists, software engineers, and stakeholders to translate business requirements into ML solutions Optimize model performance, scalability, and reliability Build and maintain data pipelines and feature engineering workflows Monitor and retrain models to ensure continued performance over … time Implement best practices for version control, testing, and CI/CD in ML systems Stay up to date with the latest advancements in machine learning and AI technologies Required Skills & Experience Strong programming skills in Python (e.g., TensorFlow, PyTorch, Scikit-learn) Experience deploying ML models using cloud ...

machine learning delivery in a role that blends technical depth with real world impact. You will work on production grade ML systems that directly improve operational and commercial outcomes, with the backing of a highly skilled, collaborative data team. The Company They are a specialist, data led organisation … learning models into live production environments Designing and maintaining MLOps workflows, including model lifecycle management Developing APIs and containerised services to support ML products Implementing DevOps best practices across development and production Collaborating cross functionally to align data, modelling, and business requirements Your Skills and Experience Strong commercial ...

hands-on engineering role, working closely with data scientists, analysts, architects, and product teams to productionise models, build data pipelines, and embed ML capabilities into live services. Key Requirements Active Security Clearance (SC) - must be current and transferable Proven experience as a Machine Learning Engineer within central government … regulated environments Strong programming skills in Python (e.g. Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) Experience building and deploying ML models into production environments Strong knowledge of cloud platforms, particularly: Azure (ML Studio, Azure ML, Data Factory, Synapse) Experience in AWS environments is beneficial Experience with MLOps practices and tools ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...

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: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong 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 ...