1 to 25 of 1,030 Permanent Machine Learning Jobs in England

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 ...

Machine Learning Engineer LOCATION- Reading TERM- Permanent SALARY- £60,000 to £90,000 per annum (plus benefits) My client is a technology-focused organisation developing advanced AI and data-driven solutions across a range of industries. They are looking to expand their technical team by hiring a Machine … models Preparing and processing datasets for model training and evaluation Improving model performance through experimentation and optimisation Collaborating with software engineers to integrate ML solutions into applications Researching and implementing new machine learning techniques where appropriate If you are interested in this position, please apply with ...

edge methods in AI, machine learning, and MLOps/LLMOps practices. You'll have the opportunity to: Work alongside leading data scientists, ML engineers, and AI researchers on national security projects Design, develop, and iterate on machine learning models for traditional ML use cases and GenAI …/LLM applications Explore and implement ML and LLM models on complex, multi-modal datasets Apply modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms Influence technical direction and best practice in ML and AI engineering Mentor and support junior engineers and graduates Engage directly ...

+ 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 ...

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 ...

Data Scientist (Machine Learning) – Initial 12 mth FTC £50,000+Bonus+Benefits-Remote working My client are a leading Consultancy in the Commercial Sales arena helping Businesses and Retailers all across the UK. Due to exciting growth we are building a new machine Learning team. With most … team in place we are looking for a Data Scientist (Machine Learning) to support the build and launch of our new Microsoft Fabric Lakehouse and machine learning platform. This is a largely remote role with on average just 1 day a month required in the office. ...

Data Scientist (Machine Learning) – Initial 12 mth FTC £50,000+Bonus+Benefits-Remote working My client are a leading Consultancy in the Commercial Sales arena helping Businesses and Retailers all across the UK. Due to exciting growth we are building a new machine Learning team. With most … team in place we are looking for a Data Scientist (Machine Learning) to support the build and launch of our new Microsoft Fabric Lakehouse and machine learning platform. This is a largely remote role with on average just 1 day a month required in the office. ...

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. ...

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 ...

both their technical platform and engineering capability. The Role They are hiring a Senior Machine Learning Engineer to take ownership of their ML strategy and help scale the company’s modelling and data capabilities. This role sits at the core of the business - bridging research, engineering, and product … applied across their discovery pipeline. You’ll be expected to lead from the front: setting technical direction, mentoring engineers, and building production-grade ML systems that integrate closely with biological research workflows. What You’ll Be Doing Lead the design and development of machine learning models applied ...

Must have active DV Clearance Up to £85k DoE plus bonuses and benefits 3 days on site per week in Cheltenham Skills required in Machine Learning, AWS/Azure, Python, NLP, AI Who are we? We are recruiting a Data Scientist with DV Clearance for a prestigious client … opportunities to develop your skillset and personal profile in an inclusive culture. What will the Data Scientist be doing? Apply creative data science and ML techniques Innovate and research solutions Stay current with ML and data tech Engage in full data science lifecycle Document technically Deliver high-quality project components ...

Machine Learning Engineer - £110k – £130k – Geospatial Tech 4 GoodMachine Learning | Deep Learning | Time Series | Climate | Remote Sensing | PyTorch | scikit-learn | Geospatial | AWS | MLOps | Python | Risk Modelling | FinTech |Do you want to work with a business building AI-native data system that bring clarity and credibility … real-world environmental challenges, helping organisations make high-impact decisions around risk, resilience and commercial performance This is the chance to join as a Machine Learning Engineer working with a climate-tech scale-up applying cutting-edge Machine Learning to satellite data, weather models and environmental ...

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 ...

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 ...