51 to 75 of 852 Machine Learning Jobs in London

commercial performance and competitive advantage. They are now seeking a Head of Data Science to define and lead the next phase of their ML capability. This is a strategic leadership role focused on building a scalable, high-impact data science function that consistently delivers measurable business outcomes. This … performance metrics, and positioning machine learning as a long‐term strategic differentiator for the organisation. Skills & Experience Experience operating at scale where ML directly influences commercial performance A track record of building and leading high‐performing data science teams Strong stakeholder management skills, with the ability to influence ...

wide variety of problem sets and encourage applications from both generalists and specialists including those who self-identify as statisticians, software engineers, machine learning practitioners, data scientists or data engineers. CANDIDATE PROFILE Please note that successful candidates will need to be eligible to undertake the DV clearance process … . In terms of the ideal candidate, we encourage applications from both generalists and specialists including those who self-identify as statisticians, software engineers, machine learning practitioners, data scientists or data engineers. You will have demonstrable experience in machine learning and be able to take initiative ...

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 ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

taking ownership of complex, Enterprise - Level AI Transformations getting Hands-On with the Engineering required to move Theoretical Models into robust, Production-Grade ML systems. Role Overview: You will be stepping in as the Technical Lead for Large - Scale Enterprise Client s across Europe. You'll advise stakeholders on complex … Fluent in English . Bonus Points for those that speak both English & Spanish to work directly with Local Stakeholders. Who Should Apply: The ML Ops Veteran: Excellent Hands-On Experience building Distributed Machine Learning Pipelines & Production ML Systems at an Enterprise Scale. The Client-Facing Engineer ...

Contract Machine Learning/Data Scientist (SC Cleared) We are seeking an experienced Machine … Learning/Data Scientist for an exciting contract opportunity. This role requires active SC clearance and a strong background in building and deploying ML solutions within cloud environments. Key Responsibilities: Develop and deploy machine learning models for anomaly detection Build proofs of concept (PoCs) to validate data ...

Title: Data Scientist/Machine Learning Engineer Location: UK Experience: 2–5 years Education: Master's in Science (IT/Computer Science/Engineer) Employment Type: Full-Time UK based candidates only. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. … Services organizations as well as Mobile Apps and Service companies. Required Skills: 2-4 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field Fluent English (written/spoken) Strong hands ...

real commercial impact from day one. As a Senior Data Scientist, you'll be working at the heart of the business, designing and deploying machine learning models that predict user behaviour, helping clients optimise for revenue, retention, and long-term value rather than just installs. This Senior Data … Experience Must have: Strong experience in machine learning/data science (typically 4-8+ years) Proven experience building and deploying ML models in production Solid understanding of: Churn modelling Propensity modelling Behavioural data analysis Strong Python skills (e.g. Pandas, NumPy, ML libraries) Experience working with real-world ...

your family again! Design reusable assets, solutions, and develop best practices for current and future business problems. Consult on complex analyses and advanced machine learning methods. Communicate and provide guidance to senior client leadership and teams. Shape AI strategy and the delivery of LLM based solutions. Operate across … production deployment. Consult on leveraging cloud platforms like AWS, Azure, and GCP to facilitate scalable model deployment. Partner with developers and engineers to deploy machine learning algorithms that drive measurable business value. Ensure Responsible and Ethical AI Collaborate with cloud vendors to integrate Responsible AI principles and standards ...

focusing on what clients really need and delivering against that every single day. Key Responsibilities Lead the development and deployment of advanced AI and machine learning models to support and enhance our workflows. Collaborate with cross-functional teams to integrate AI technologies with other system components. Ensure … Qualifications Extensive experience with version control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models ...

growing data science and AI consulting capability. You will work on complex, high impact problems across public and private sector clients, applying data science, machine learning and generative AI to deliver measurable, real world outcomes. You will also contribute to developing people, standards and culture within a rapidly … partners and stakeholders to shape, deliver and embed data driven solutions that make a tangible difference. Key responsibilities include: Designing and delivering data science, machine learning and generative AI solutions to solve real business and operational problems. Leading technical workstreams within larger client programmes, from problem definition through ...

Learning Engineer to design, build, and productionise machine learning models for our innovative matching platform. You will work across the entire ML lifecycle, from feature engineering to deployment automation, ensuring the optimisation and explainability of inference processes. Collaborating closely with data scientists and product teams, your role … architectures. Develop fallback feature flows and implement robust data quality checks. Develop ranking, scoring, and entity-similarity models for the matching platform. Use modern ML model frameworks such as PyTorch, TensorFlow, or XGBoost. Apply SHAP or similar techniques to generate interpretable model explanations. Build and maintain training, processing, and inference ...

Machine Learning Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines … with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale. What Youll Work On ML lifecycle infrastructure Productionizing models: packaging, deployment, versioning, and rollback Designing CI/CD pipelines ...

machine learning models used across financial data, risk, and automation use cases. You’ll work alongside engineers and product teams to deploy ML solutions into production. Key Responsibilities Develop and deploy ML models Work with structured financial datasets Collaborate with engineering teams Improve model performance and monitoring Support … production ML pipelines Required Experience Machine learning engineering experience Python and ML frameworks Experience deploying models to production Financial services or data-heavy background Cloud ML tooling exposure Nice to Have NLP or time-series modelling MLOps experience Risk or fraud use cases Why Join Applied ML ...