76 to 100 of 995 Machine Learning Jobs in London

applied machine learning solutions that power far-field voice experiences across connected devices and cloud platforms. Design, develop, train, and optimise scalable ML models for far-field voice detection, verification, and enhancement across device and cloud platforms. Contribute to innovation discussions and research in applied speech, audio signal … processing, ASR, NLP, and machine learning. Build cloud-based ML pipelines and APIs that process real-time audio streams at scale. Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences. Develop and document technical specifications, ensuring solutions meet latency ...

available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Central London 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/ ...

Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank’s broader AI strategy and long-term objectives. The role combines strong technical leadership with a clear focus on delivery outcomes, ensuring … strategic direction while taking accountability for translating this into practical, high-quality engineering outcomes across squads. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with the Bank’s AI strategic vision, as set out by the AI Capability Lead ...

influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you'll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using … best practices from the ground up Collaborating closely with product, engineering, and leadership What we're looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start ...

Principal Machine Learning Engineer to play a key role in shaping the architecture, strategy, and delivery of large-scale production ML systems powering live sports environments. This is a genuinely high-impact opportunity for someone who enjoys solving complex real-time engineering challenges while influencing technical direction across … platform teams. Key areas of focus include: Real-time sports insights & personalisation Computer vision & multimodal AI Live event detection & metadata generation Low-latency ML inference systems End-to-end MLOps & production ML Scalable cloud-native AI platforms What they’re looking for: Strong experience leading ML engineering initiatives in sports ...

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 ...

ASOS is seeking a Senior Machine Learning Engineer to join their Personalisation team in Greater London. In this role, you will design and run machine learning systems that enhance customer experience and empower personal style. You'll collaborate with engineers and data scientists to deploy … improve machine learning models at scale. We seek candidates with professional experience in machine learning, particularly deep learning, and the ability to mentor junior team members. Expect a dynamic environment that fosters innovation and growth. #J-18808-Ljbffr ...

research models for production use Design and maintain scalable inference pipelines for edge‐deployed systems Collaborate with backend and product teams to integrate ML solutions into production platforms Contribute to architectural decisions and technical direction within the ML/CV stack Support deployment and optimisation workflows for production inference systems … geometry Experience deploying machine learning and computer vision models into production environments Hands‐on experience with PyTorch, Torchvision, OpenCV, and related ML tooling Experience optimising inference pipelines and working with deployment frameworks such as ONNX or TensorRT Ability to evaluate academic research and translate findings into practical product ...

customers. We’re not about selling products – we want to solve problems and change lives through Monzo. About the role The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and statistical modelling. We have a primary … focus on credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing. Responsibilities Own multiple ML applications end‐to‐end, from experiment design and data curation to deployment and monitoring. Collaborate with Credit Strategy Managers, Model Validation Analysts, Backend Engineers and Product Managers ...

defence environments. This is an opportunity to work at the cutting edge of data science, focusing on GenAI, large language models, and cloud-based ML deployments, while also taking on leadership responsibilities within a growing team. Role Responsibilities Lead day-to-day technical delivery across data science and ML projects … data governance and security best practices Desirable Skills Experience using GPUs in cloud environments Knowledge of MLOps, CI/CD pipelines, and monitoring ML models Experience building APIs and working with modern DevOps practices Eligibility Requirements Due to the nature of the work, candidates must: Hold active DV clearance ...

defence environments. This is an opportunity to work at the cutting edge of data science, focusing on GenAI, large language models, and cloud-based ML deployments, while also taking on leadership responsibilities within a growing team. Role Responsibilities Lead day-to-day technical delivery across data science and ML projects … data governance and security best practices Desirable Skills Experience using GPUs in cloud environments Knowledge of MLOps, CI/CD pipelines, and monitoring ML models Experience building APIs and working with modern DevOps practices Eligibility Requirements Due to the nature of the work, candidates must: Hold active DV clearance ...

Cloud/AI/ML/Transformation/Agile Role: Project Manager (Contract) - AI/Machine Learning Programme Day Rate: Up to 585 a day (Inside IR35) Contract Length: Until March 2027 (extension likely) Location: Hybrid - 2-3 days per week onsite (London) Start: ASAP Overview … looking for an experienced Project Manager to support the delivery of a machine learning proof-of-concept within a large-scale operational environment. This is a high-impact role focused on stakeholder coordination, system integration, and delivery of AI-driven insights, with strong potential to expand into broader ...

Gigaton is seeking a Senior Machine Learning Engineer to develop models that drive our innovative AI solutions aimed at reducing carbon emissions. You will play a crucial role in a collaborative environment, contributing to both engineering and research efforts in machine learning. Your responsibilities include building machine learning models, collaborating with product teams, and establishing best practices. A passion for climate change mitigation and expertise in Python and machine learning techniques are essential. #J-18808-Ljbffr ...

ways Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization Actively contributed to a strong community of machine learning practitioners at Spotify Who You Are An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications Hands ...

models directly influencing commercial decisions at scale. The role is heavily focused on machine learning engineering, particularly around time-series forecasting, scalable ML systems, feature stores, and MLOps. There’s also some exposure to generative AI and LLM-related work, but this is primarily a deeply technical ML … systems at scale. The setup is hybrid with two days per week onsite in London. Experience around forecasting, time-series modelling, recommendation systems, production ML infrastructure, or large-scale MLOps environments would all be highly relevant. Salary: £100,000 - £120,000 plus equity and benefits. APPLY NOW for immediate consideration. ...

, optimisation and operational research techniques Strong Python expertise with experience delivering production‐quality data science software Experience working with cloud platforms and modern ML tooling Strong software engineering discipline including testing, CI/CD and version control Ability to structure complex business and technical problems and propose pragmatic solutions … Curiosity, resilience and adaptability in fast‐moving environments Strong commitment to delivering measurable business value Experience Master’s degree or greater in data science, ML, or operational research, or 6+ years of highly relevant industry experience (required) 4-6 years working on production ML or optimization software products at scale ...

, optimisation and operational research techniques Strong Python expertise with experience delivering production‐quality data science software Experience working with cloud platforms and modern ML tooling Strong software engineering discipline including testing, CI/CD and version control Ability to structure complex business and technical problems and propose pragmatic solutions … resilience and adaptability in fast‐moving environments Strong commitment to delivering measurable business value Your experience: Master’s degree or greater in data science, ML, or operational research, or 6+ years of highly relevant industry experience (required) 4-6 years working on production ML or optimization software products at scale ...

professionals to design, implement, and evaluate AI driven solutions. The successful candidate will be responsible for transforming complex healthcare data into meaningful insights, developing machine learning models, supporting clinical decision making, and ensuring that AI systems are safe, reliable, and aligned with ethical and regulatory standards. This position … innovation can have a direct and measurable impact on the quality of care provided to patients. Key Responsibilities Design, develop, and deploy AI and machine learning solutions for healthcare applications. Analyze clinical, operational, and patient data to identify opportunities for AI-driven improvements. Build predictive models, decision-support ...