1 to 25 of 79 Machine Learning Jobs in the South West

+ 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 ...

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. ...

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 ...

analytics and modelling. Apply LLMs, embeddings and natural language processing techniques to enhance analytical capability and insight. Build and support cloud-based data and ML workflows using Azure, Microsoft Fabric or equivalent platforms. Translate business problems into clear analytical and technical specifications, ensuring solutions align with user needs. Communicate complex … STEM degree or equivalent experience, with a strong mathematical, analytical or software-focused background. Proven experience using Python, SQL and SparkSQL in data or ML-focused roles. Strong understanding of machine learning concepts and experience using common ML libraries such as scikit‐learn, TensorFlow or PyTorch, alongside packages ...

Machine Learning Engineer to join a growing advanced analytics and AI capability. This is a hands-on engineering role building and deploying ML solutions in highly secure, data-rich environments , where work directly contributes to national-level outcomes. Why this role? This is an opportunity to work … infrastructures Supporting the development of AI-driven capabilities for mission-critical systems Collaborating with engineers, data scientists, and security specialists Contributing to the full ML lifecycle from data prep to deployment What you’ll be doing Develop and implement machine learning models and pipelines Work with structured ...

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 ...

What you will do as a Senior ML Engineer Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics. Own the ML lifecycle from data preparation through training, evaluation, and deployment. Implement and maintain MLOps workflows for continuous integration and delivery of ML models. … Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability. Contribute to architecture decisions for ML pipelines and data flows. Apply secure coding and configuration practices in line with compliance standards. Mentor junior engineers and share best practices across the team. Support innovation by researching emerging ML ...

ability to work with both technical and non-technical stakeholders It would be an advantage if you also have: Experience supporting data science or machine learning initiatives Experience with BI tools such as Tableau or Power BI Familiarity with big data tools such as Spark or Hadoop Knowledge … compliance. Establish processes for, and participate in code reviews, testing and documentation to ensure the deployment of high-quality models and solutions. Analytics and Machine Learning Support To support data analysis, data preparation, and feature engineering to identify trends and patterns. To support and contribute to the development ...

moving notebooks into production”. We’re looking for a Senior Machine Learning Engineer to help design, build, and deploy mission‐critical ML systems used across defence, security, and high‐integrity public sector programmes . You’ll be working on problems where correctness, robustness, and trust matter … much as raw performance — and where your work has real‐world impact at national scale . 🔥 Why This Role Is Different Real ML engineering : production systems, not demos Work on secure, high‐integrity platforms where ML decisions matter Influence architecture , not just implementation Join a team that treats ML ...

levels available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Cheltenham Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

levels available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Cheltenham Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – 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 click apply for full job details ...

site role located in Bristol, United Kingdom for a Senior Machine Learning Engineer. The selected candidate will be responsible for: Architecting the ML Solver Platform : Define modular architecture for data preprocessing, model execution, and post-processing. Establish clear API contracts between Python/TensorFlow and C# services. Design … develop, and implement advanced machine learning algorithms and models, focusing on pattern recognition and neural network applications Productionizing ML Workflows : Convert research code into robust, testable, and observable services. Implement CI/CD pipelines, automated testing, and reproducibility standards. Integration & Interoperability : Design REST/gRPC endpoints for cross ...

critical challenges to the UK’s digital landscape. As a Principal Data Scientist you will: Lead on the continual development of Automation, Orchestration and Machine Learning capabilities Be a People Leader and manage 4-6 individuals Undertake pre-processing of structured and unstructured data Lead … development of predictive models and machine-learning algorithms Coach/mentor junior members of the team What you’ll bring UK DV Clearance or the ability obtain it (https://www.gov.uk/government/publications/united-kingdom-security-vetting-clearancelevels/national-security-vetting-clearance-levels ...

innovative data science initiatives and deliver meaningful, real-world outcomes. The Role You will take ownership of technical delivery and design end-to-end machine learning solutions. Operating within a collaborative, agile environment, you’ll address complex problems using advanced analytics and AI-driven approaches. Key Responsibilities Lead … initiatives across machine learning, automation, and analytics Oversee and mentor a small team of data scientists Build predictive models and data-driven solutions (structured and unstructured data) Collaborate with stakeholders and translate technical findings into business impact About You Proven experience in a senior data science position Strong ...

cutting-edge software at scale for both customer infrastructure and public cloud environments. With a strong heritage of innovation and expertise in Data Science, Machine Learning, Agile Software Development, Security Assurance, and Cryptographic Technologies, we help organisations overcome complex data challenges and drive digital transformation. What Will … Doing? As a Data Science Lead, you will be at the forefront of technically leading diverse teams across machine learning, cloud, data engineering, DevOps, and software engineering. You will: Lead customer engagements and manage stakeholder relationships Contribute to and prepare technical bids and proposals Collaborate with Delivery Management ...

solving skills to collaborate effectively with cross-functional teams. Awareness of security principles and best practices to ensure secure data solutions. Commitment to continuous learning and staying current with Azure, Databricks and data engineering trends. Strong experience working within an agile development methodology, ideally Scaled Agile (SAFe or similar … technical/scientific subject (or equivalent experience). Microsoft Azure Data Engineer or Solutions Architect certification (desirable). Databricks Certified Data Engineer or Machine Learning Associate (desirable). Experience with streaming solutions (Kafka, Event Hubs, Spark Streaming) (desirable). Knowledge of machine learning ...