76 to 100 of 958 Machine Learning Jobs in England

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 ...

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 ...

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 ...

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 ...

successfully transition into robust, enterprise-grade systems within a modern, cloud-native environment. Responsibilities: Contribute to the evolution of our Data Science platform, defining ML Engineering best practices, tooling and architecture as our team and portfolio grow. Drive automation across the end-to-end data science lifecycle using CI/… infrastructure-as-code to support scalable production workflows. Collaborate across the full model development and deployment lifecycle, spanning traditional ML and generative AI solutions. Work closely with data engineers, software engineers and wider business teams to deliver impactful, production-ready ML services. Write clean, maintainable, high-quality Python code following ...

with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using SQL 🚀 Support the deployment and monitoring of models in production environments 🤝 Collaborate … years of experience in AI, machine learning, or software/data engineering (including internships, placements, or academic projects) 🐍 Strong Python skills for ML and data processing 🗄 Experience working with SQL and structured datasets ☁️ Familiarity with cloud platforms and modern data stacks 🧠 A solid understanding of machine learning ...

Machine Learning Engineer | Early Stage Deep Tech Start Up | London I am partnered with an early stage, London based start up that is building an AI native intelligence layer for private market investing. The platform transforms fragmented documents, deal histories, and proprietary investment data into structured, searchable intelligence … private equity, venture capital, and private credit teams. They are hiring a Founding Machine Learning Engineer to join at early stage, with real ownership over both the core technology and the product direction. This role suits someone with a strong academic background from a leading university , alongside clear ...

Title: AI/ML Research Engineer (London, UK) Location : Must be based London, UK Employment Type : Permanent Work Model : Hybrid (London) Introduction: Our client (international) is a collection of engineers and designers who want the world to connect beautifully. Their team first came together to build one of the world … every day and they're putting this knowledge to work, engineering and designing better ways to connect. They are establishing a new AI/ML engineering team in London to extend these capabilities. This is a foundational role, you will be among the first hires, helping to shape the technical ...

responsible for the "factory" that allows our models to live, breathe, and perform in high-pressure production environments across various industries. Key Responsibilities ML Systems Architecture: Design and implement the end-to-end lifecycle of ML models, including automated retraining, model versioning, and monitoring systems. Productionalization: Take validated prototypes from … significant plus. Tooling & Orchestration: Deep experience with containerization (Docker, Kubernetes) and orchestration tools like Kubeflow, Airflow, or Metaflow. Cloud Architecture: Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing ...

model performance over time Contribute to data pipelines, model training workflows, and MLOps practices Stay up to date with the latest developments in AI, ML, and data science Document models, experiments, and technical decisions clearly Requirements Master’s degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related field Strong foundations in machine learning, algorithms, and statistics Experience with Python and common ML libraries (e.g. TensorFlow, PyTorch, scikit-learn) Understanding of software engineering fundamentals and version control (e.g. Git) Ability to communicate technical ideas clearly to both technical ...

Data Scientist Specialist , you will: Work at the forefront of GenAI, machine learning, and advanced analytics Design, build, and deploy LLMs and ML models in cloud and high-performance computing environments Lead day-to-day technical delivery on projects, supporting and guiding small teams … continuous improvement, innovation, and knowledge sharing Support the performance management and development of junior team members Key Responsibilities Design and deploy secure, scalable ML and GenAI solutions Apply robust software engineering practices to data science delivery Build reproducible ML pipelines using modern MLOps practices Ensure solutions align with data governance ...

Lead Machine Learning Engineer Up to 145k Xcede has just partnered with one of the UK’s most established applied AI companies to support the growth of their senior engineering leadership team. This is a principal-level technical role for someone who wants to shape how large-scale … delivery programmes Confident communicator able to influence executive stakeholders and align business and engineering priorities If you are interested in this or other Lead Ml Engineering positions, please contact Gilad Sabari @ gilad.sabari@xcede.com ...

, and operations research (linear, mixed integer programming, heuristics) Fluent in Python(required) and other programming languages (preferred)with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobietc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms … preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have Experience in code testing (unit, integration ...

this role! You'll help lead and implement the improvement of algorithms, optimising execution, usability, and package architecture of our ML Verification packages. Note that this is a Python code focused role, rather than a Data Science role, so Python programming skills are the priority, where as Machine Learning … systems we build are safe to use. To meet this need, we are developing advanced deep validation techniques and tools that allow AI/ML engineers world-wide to validate the robustness of their models, as well as repair the fragilities that they discover. By joining ...