1 to 25 of 2,388 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 Research Engineer - NLP/LLM An incredible opportunity for a Machine Learning Research Engineer to work on researching and investigating new concepts for an industry-leading, machine-learning software company in Cambridge, UK. This unique opportunity is ideally suited to those with … cutting-edge, machine-learning software A good remuneration and benefits package Applications: If you would like to apply for this unique ML Engineer opportunity, we would love to hear from you. Please send an up-to-date CV via the relevant link. Were committed to creating an inclusive ...

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 ...

objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform. … systems, offering the chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM solutions Leading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with ...

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 ...

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 … good fit if you: 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 ...

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 ...

Specialists, and we're hoping it's you! In this role, you'll play a leading role in helping both customers with their ML validation challenges and in helping drive our product forward with insights on how to build the best validation solutions for high-stakes machine vision … problems. The specific focus of this position is on ML-based computer vision in high-stakes applications in Aviation, Mobility, Robotics and Edge Devices, with particular emphasis on object detection and tracking. The role has customer & user-facing elements working on real world problems to help ML teams ...

Specialists, and we’re hoping it’s you! In this role, you’ll play a leading role in helping both customers with their ML validation challenges and in helping drive our product forward with insights on how to build the best validation solutions for high-stakes machine vision … problems. The specific focus of this position is on ML-based computer vision in high-stakes applications in Aviation, Mobility, Robotics and Edge Devices, with particular emphasis on object detection and tracking. The role has customer & user-facing elements working on real world problems to help ML teams ...

products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale. You'll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity … Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000 Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning. Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy ...

products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale. You’ll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity … Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000 Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning. Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy ...

products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale. You’ll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity … Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000 Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning. Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy ...

products through advanced machine learning models improving search relevance, personalisation, and conversion outcomes at scale. You’ll lead a talented team of ML Scientists and collaborate cross-functionally with product, data, and engineering leaders to define and execute the ML roadmap for search. This is an opportunity … Learning, Marketplace, Ecommerce, | 35 Million Users | London, Hybrid, 1 Day PW, Up to £140,000 Lead, coach, and develop a team of ML Scientists, fostering a culture of experimentation, collaboration, and continuous learning. Partner with Product, Data, and Engineering leaders to shape and deliver an actionable ML strategy ...

/Machine Learning Engineer/Staff Machine Learning/Location: UK (Hybrid or Remote options available) Salary: £60,000 £100,000 per annum (depending on experience) Type: Permanent Recruitment Partner: 167 Solutions Ltd The Opportunity 167 Solutions is working with a forward-thinking organisation that … investing heavily in artificial intelligence and data-driven products. This role sits at the heart of that growth and will suit an AI/Machine Learning Engineer who enjoys taking models from concept through to production. You will work closely with software engineers, data teams, and product stakeholders ...

Machine Learning Researcher (PhD Statistics Python AI R&D) Cambridge/WFH to £85k Are you a tech savvy, PhD educated, Machine Learning Researcher looking for an opportunity to work on complex and interesting systems at the cutting edge … technology? You could be progressing your career working on real-world problems within a high successful SaaS tech company that provides AI and ML products for automotive innovators to design better cars faster and achieve greater sustainability through Machine Learning. As a Machine Learning Researcher you will ...

Machine Learning Engineer, you’ll work closely with Data Scientists, Data Engineers and delivery teams to productionise models and build robust, scalable ML systems within client environments. This role is highly hands-on, with a strong focus on deployment, performance and reliability. Key Responsibilities Translating data science models … into scalable, production-ready machine learning solutions. Designing and building end-to-end ML pipelines, from data ingestion to deployment and monitoring. Collaborating with data engineers on data architecture, pipelines and feature stores. Working closely with data scientists to productionise models and improve performance. Deploying, monitoring and maintaining ...

Machine Learning Engineer, you'll work closely with Data Scientists, Data Engineers and delivery teams to productionise models and build robust, scalable ML systems within client environments. This role is highly hands-on, with a strong focus on deployment, performance and reliability. Key Responsibilities Translating data science models … into scalable, production-ready machine learning solutions. Designing and building end-to-end ML pipelines, from data ingestion to deployment and monitoring. Collaborating with data engineers on data architecture, pipelines and feature stores. Working closely with data scientists to productionise models and improve performance. Deploying, monitoring and maintaining ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...