7 Reinforcement Learning Jobs in London

Machine Learning Engineer £70-120k + benefits London Hybrid Why Join? AI/ML driven business Innovation is core to business success Global leader in this space with leading international orgs as customers Forge your career path, opportunity to follow leadership or senior IC positions Work with people … from across the globe Create and improve innovative products with a real world impact Responsibilities: Research, design, and implement machine learning algorithms and models to address business challenges and opportunities. Collect, preprocess, and analyze large datasets to extract meaningful insights and features. Develop and deploy scalable machine learning … scientists, mlops engineers and product managers to define requirements and deliver solutions that meet business objectives. Stay current with the latest developments in machine learning and related fields, and apply cutting-edge techniques to enhance our capabilities. Requirements: Solid understanding of machine learning concepts and techniques, including supervised more »

product and engineering teams across the globe. The Intelligent Systems team is at the forefront of driving innovation through cutting-edge data science, machine learning, and generative AI technologies. As a crucial part of our organization, this team is poised for substantial growth in the coming year and beyond. … development life cycle. Automating quality assurance processes and cloud resource allocation in software development. Requirements PhD or advanced Masters in Statistics, Computer Science, Machine Learning & AI, Mathematics, or Physics. Hands-on experience in at least three of the following areas: Generative AI, Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Recommendation Systems, Knowledge Graphs, Probabilistic Inference, Bayesian Statistics, Reinforcement Learning. Strong industry experience, with a focus on taking concepts and models from conception to production and quantifying business impact. Proficiency in Python programming. Expertise in GIT and the data science Python stack. Experience with real-world more »

Pattern - Hybrid 2days per week in the Vitality London Office.Full time, 37.5 hours per week. Top 3 skills needed: Delivery of high-impact machine learning projects Stakeholder management and collaboration Identification of new project opportunities What this role is all about: At Vitality, data scientists develop and deploy machine … learning models that help us realise our core purpose and achieve our ongoing business objectives. Our data scientists work on innovative applications of machine learning techniques spanning the entire value chain of our business. They work with rich datasets, and on project use cases spanning a broad variety … new projects in an innovative environment thats focused on making our members healthier and enhancing and protects their lives. Key Actions Implementing the machine learning life cycle: building models in a structured manner following best practice in the collection and analysis of modelling data, feature engineering, model fitting, selection more »

insights to help them harness the full potential of AI within their organizations. Mentoring and guiding junior team members, fostering a culture of continuous learning and innovation. REQUIREMENTS: An education in Computer Science, Engineering, Mathematics, or a related discipline Demonstrated success in designing and delivering AI solutions within the … insurance domain , Hands-on experience across predictive modelling, natural language processing, computer vision, and reinforcement learning. Proficiency in ML frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, GCP). Thorough comprehension of insurance business processes and regulatory frameworks, with the ability to more »

insights to help them harness the full potential of AI within their organizations. Mentoring and guiding junior team members, fostering a culture of continuous learning and innovation. REQUIREMENTS: A Bachelor's degree in Computer Science, Engineering, Mathematics, or a related discipline; advanced degree preferred. Demonstrated success in designing and … delivering AI solutions within the insurance domain , with hands-on experience across predictive modeling, natural language processing, computer vision, and reinforcement learning. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, GCP). Thorough comprehension of insurance business more »

researchers from various disciplines. Responsibilities : Research and Development: Stay updated with the latest advancements in AI, specifically focusing on Large Language Models (LLMs) and Reinforcement Learning (RL). Develop and implement innovative solutions to improve existing systems or create new ones. Model Training and Integration : Train and integrate … machine learning models, with a particular focus on LLMs. Utilise techniques such as transfer learning and fine-tuning to adapt pre-trained models to specific tasks or domains. Engineering : Apply strong coding skills in Python to develop and maintain robust, scalable systems. Follow object-oriented design principles and … positive and collaborative team environment. MLOps and Deployment : Apply knowledge of MLOps principles and practices to streamline the development, deployment, and monitoring of machine learning systems. Deploy ML models into production environments. Requirements : Master's or PhD in Computer Science, Engineering, or a related field. 5+ years' experience with more »

researchers from various disciplines. Responsibilities : Research and Development: Stay updated with the latest advancements in AI, specifically focusing on Large Language Models (LLMs) and Reinforcement Learning (RL). Develop and implement innovative solutions to improve existing systems or create new ones. Model Training and Integration : Train and integrate … machine learning models, with a particular focus on LLMs. Utilise techniques such as transfer learning and fine-tuning to adapt pre-trained models to specific tasks or domains. Engineering : Apply strong coding skills in Python to develop and maintain robust, scalable systems. Follow object-oriented design principles and … positive and collaborative team environment. MLOps and Deployment : Apply knowledge of MLOps principles and practices to streamline the development, deployment, and monitoring of machine learning systems. Deploy ML models into production environments. Requirements : Master's or PhD in Computer Science, Engineering, or a related field. 5+ years' experience with more »