26 to 50 of 181 Deep Learning Jobs in England

Machine Learning Engineer (Energy Sector Focus) Our client is seeking a highly skilled and experienced Machine Learning Engineer to join their data science and AI team. This role is critical for leveraging cutting-edge machine learning and AI techniques to optimise operations, enhance exploration and production efficiency, drive the energy transition and improve decision-making across the … and demonstrated prior experience working within the energy, oil, and gas, or a related industrial sector . Key Responsibilities Design, develop, and deploy robust, scalable, and production-ready machine learning models and pipelines for various energy-sector applications Collaborate with domain experts (geoscientists, reservoir engineers, operational technologists) to understand complex business problems and translate them into actionable ML solutions. … sparse energy-related datasets. Evaluate and optimize model performance, ensuring high accuracy, reliability, and interpretability in a high-stakes operational environment. Stay current with the latest advancements in machine learning, deep learning, and MLOps to continuously improve AI capabilities. Ensure compliance with data privacy, security, and operational safety standards. Essential Qualifications Bachelor's or Master's degree More ❯

you'll be shaping the future of secure data systems and AI capabilities in some of the most critical areas of the UK's national infrastructure. As a Machine Learning Engineer, you'll be part of a forward-thinking team solving complex, real-world challenges through advanced analytics, automation, and intelligent systems. This is your chance to work on … with bespoke Operational Technology, all in a fast-paced, collaborative environment. We're looking for curious, creative minds-people who are not only technically skilled in Python and machine learning but also eager to explore, learn, and build secure, scalable AI solutions. Responsibilities Building, integrating, testing and scaling models including NLP and Computer Vision. Take ownership of developing, training … and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance. Developing deep learning architectures and implementing neural networks tailored to complex use cases. Implementing and maintaining MLops workflows Collaborating closely with Data Engineers and DevOps teams to support continuous integration, deployment, and automation. Exploring new tools and frameworks to keep your solutions modern More ❯

About this role Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group who use our expertise to derive insights from complex data, working in close collaboration with our business partners. This role will primarily focus … on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting. What you'll do Develop and maintain the machine learning models which define our competitive advantage in the financial services market. Explore and evaluate data, using advanced feature generation and categorisation techniques, in … data and extract actionable solutions, working cross-functionally to support key business initiatives and drive sustainable growth. What we're looking for A strong understanding of probability, statistics, machine learning, feature extraction and familiarity with large data set manipulation. Experience using deep learning models, particularly for sequential data. Experience working with Open Banking or Credit Bureau data. More ❯

The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL). - Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions. - Design and conduct hypothesis testing (A …/B and multivariate testing) and apply causal inference methodologies. - Perform exploratory data analysis, feature engineering, and develop models across traditional statistical and deep learning architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation … years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering More ❯

The team leverages technology and AI to enhance, not replace, human creativity and insight. Responsibilities - Lead end-to-end execution of complex data science projects integrating statistical modelling, machine learning (ML), and deep learning (DL). - Collaborate closely with cross-functional teams (product, engineering, business stakeholders) to deliver data-driven solutions. - Design and conduct hypothesis testing (A …/B and multivariate testing) and apply causal inference methodologies. - Perform exploratory data analysis, feature engineering, and develop models across traditional statistical and deep learning architectures. - Establish modelling frameworks with statistical quality control, detecting drift and decay. - Drive best practices for model explainability (e.g., SHAP/LIME) and scalable ML systems (including generative AI, NLP, CV, and recommendation … years in data science with at least 2 years leading teams. - Proven success in production deployment of ML/LLM/NLP/CV models. - Strong understanding of machine learning fundamentals, statistical inference, and model evaluation. - Advanced proficiency in SQL (e.g., PostgreSQL, ELT/ETL) and Python (PyTorch, LightGBM, Scikit-learn). - Experience with modern AI concepts: prompt engineering More ❯

Lead Data Scientist | London | Multiple Sectors 📍 London (Hybrid) 💰 Up to £120,000 + Equity + Private Health Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI I’m currently looking for: 1 x Lead Data Scientist (Financial Services) 1 x Lead Data Scientist (Retail) 1 x Lead Data Scientist (SaaS) Our client partners with some of the … deliver innovative, data-driven solutions that transform customer experience, strategy, and performance. From global enterprises to digital-first disruptors, they help businesses harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly changing market. If you’re looking for an opportunity to shape the future of applied AI across exciting industry sectors, this … a trusted advisor to senior stakeholders — defining approaches to complex data challenges, guiding enterprise-scale AI applications, and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record More ❯

Lead Data Scientist | London | Multiple Sectors 📍 London (Hybrid) 💰 Up to £120,000 + Equity + Private Health Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI I’m currently looking for: 1 x Lead Data Scientist (Financial Services) 1 x Lead Data Scientist (Retail) 1 x Lead Data Scientist (SaaS) Our client partners with some of the … deliver innovative, data-driven solutions that transform customer experience, strategy, and performance. From global enterprises to digital-first disruptors, they help businesses harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly changing market. If you’re looking for an opportunity to shape the future of applied AI across exciting industry sectors, this … a trusted advisor to senior stakeholders — defining approaches to complex data challenges, guiding enterprise-scale AI applications, and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record More ❯

analytics and empower business teams to access and use data confidently Responsible Artificial Intelligence & Automation Identify, evaluate, and deliver AI initiatives including: Conversational AI (e.g., chatbots, virtual assistants) Machine Learning and Predictive Models for forecasting and optimization Collaborate with product, operations, and technology teams to embed AI into products, services, and workflows Drive process optimization initiatives using AI insights … AI/automation specialists Develop and deliver education and training programs on data literacy, analytics, and AI best practices Stay abreast of emerging trends and technologies in AI, machine learning, cloud platforms, and analytics to inform strategic decisions Your Profile Master's degree or PhD in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related … Demonstrated success in deploying AI, automation, and predictive analytics initiatives that drove measurable business outcomes Strong knowledge of enterprise architecture, data governance, and platform delivery methodologies (Agile/DevOps) Deep expertise in: Machine learning, deep learning, NLP, computer vision Data engineering, big data platforms, and analytics AI/ML model lifecycle management (MLOps) Cloud-native architectures More ❯

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. **Inside IR35, 4 days a week on site** The role:To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists … pipelines and scalable model infrastructure for production deployment Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets Collaborate closely with cross-functional teams, including traders, data engineers, and software developers What We're … hedge fund, or tech firm Advanced degree (PhD or Master's) in Computer Science, Mathematics, Physics, Engineering, or related discipline Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL Expert-level programming skills in Python and strong understanding of software engineering best practices Experience deploying ML models to production in real More ❯

Clearance Junior to Lead 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 and enhanced DV Clearance for a prestigious client … to develop your skillset and personal profile in an inclusive culture. What will the Data Scientist be doing? Our client is seeking individuals with strong technical expertise in machine learning, GenAI, computer vision, and data science, alongside solid skills in solution architecture and software engineering to design and scale impactful solutions. This role involves working closely with clients to … also opportunities to publish whitepapers and represent the organisation at conferences, all within an inclusive and diverse working environment. Key Skills and Requirements Proficient in AI techniques including machine learning, GenAI, NLP, deep learning, graph analytics, and time series analysis. Strong communicator with the ability to simplify complex concepts, manage stakeholders, and motivate/lead Agile teams More ❯

quickly embed within the organisation, lead complex projects, and provide advanced analytical insights that drive measurable business outcomes. Key Responsibilities Model Development & Deployment: Design, build, and deploy scalable machine learning and statistical models for use cases such as pricing optimisation, customer behaviour prediction, and risk modelling. Data Exploration & Feature Engineering: Work with structured and unstructured data to uncover patterns … models. Stakeholder Engagement: Collaborate with Technology, Product, Risk, and Marketing teams to translate business challenges into actionable data science solutions. Innovation & Best Practices: Apply cutting-edge techniques in machine learning, deep learning, and generative AI where appropriate. Ensure models meet standards for fairness, transparency, and compliance. Performance Monitoring: Implement model evaluation frameworks and monitor performance in production … environments. Knowledge Transfer: Document processes and share insights to enable continuity post-contract. Skills & Experience Required Advanced degree (Master’s or PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related field. 5+ years of experience in data science roles, with proven expertise in: Machine learning (supervised/unsupervised), time series forecasting, deep learning. Programming in More ❯

quickly embed within the organisation, lead complex projects, and provide advanced analytical insights that drive measurable business outcomes. Key Responsibilities Model Development & Deployment: Design, build, and deploy scalable machine learning and statistical models for use cases such as pricing optimisation, customer behaviour prediction, and risk modelling. Data Exploration & Feature Engineering: Work with structured and unstructured data to uncover patterns … models. Stakeholder Engagement: Collaborate with Technology, Product, Risk, and Marketing teams to translate business challenges into actionable data science solutions. Innovation & Best Practices: Apply cutting-edge techniques in machine learning, deep learning, and generative AI where appropriate. Ensure models meet standards for fairness, transparency, and compliance. Performance Monitoring: Implement model evaluation frameworks and monitor performance in production … environments. Knowledge Transfer: Document processes and share insights to enable continuity post-contract. Skills & Experience Required Advanced degree (Master’s or PhD) in Data Science, Machine Learning, Statistics, Computer Science, or related field. 5+ years of experience in data science roles, with proven expertise in: Machine learning (supervised/unsupervised), time series forecasting, deep learning. Programming in More ❯

Machine Learning Research Engineer Location: London (Hybrid) Salary: Competitive + Benefits We’re working with a rapidly growing AI company developing cutting-edge technology that enhances real-time voice and audio communication. Their products use advanced deep learning and signal processing techniques to isolate speech and remove background noise, improving clarity and focus across a range of … industries, from enterprise software to high-performance environments. They’re now looking for a Machine Learning Research Engineer to join their R&D team in London. The successful candidate will work at the intersection of machine learning, signal processing, and real-time systems , developing and deploying novel models that push the limits of audio intelligence. Responsibilities: Research and … prototype deep learning models for speech enhancement and separation. Design and optimise training pipelines using large-scale audio datasets. Collaborate with engineering teams to deploy models into real-world, low-latency environments. Stay up to date with new research and contribute to the company’s IP. Requirements: Background in audio or speech-related ML (e.g., noise suppression, source More ❯

Machine Learning Research Engineer Location: London (Hybrid) Salary: Competitive + Benefits We’re working with a rapidly growing AI company developing cutting-edge technology that enhances real-time voice and audio communication. Their products use advanced deep learning and signal processing techniques to isolate speech and remove background noise, improving clarity and focus across a range of … industries, from enterprise software to high-performance environments. They’re now looking for a Machine Learning Research Engineer to join their R&D team in London. The successful candidate will work at the intersection of machine learning, signal processing, and real-time systems , developing and deploying novel models that push the limits of audio intelligence. Responsibilities: Research and … prototype deep learning models for speech enhancement and separation. Design and optimise training pipelines using large-scale audio datasets. Collaborate with engineering teams to deploy models into real-world, low-latency environments. Stay up to date with new research and contribute to the company’s IP. Requirements: Background in audio or speech-related ML (e.g., noise suppression, source More ❯

the development and execution of Wolverine Worldwide's enterprise-wide AI strategy, driving innovation in product development, supply chain optimization, customer engagement, and operational efficiency. The ideal candidate combines deep expertise in AI/ML with strategic vision and cross functional leadership to scale responsible, impactful AI adoption across all business functions. Primary Duties This leadership role will drive … AI driven innovations in product & supply chain optimization, customer insights, digital transformation, and operational efficiencies. The ideal candidate will have deep expertise in AI and machine learning, a strong understanding of product, marketing, and retail operations, combined with the leadership ability to scale AI adoption across the organization. Develop and execute Wolverine Worldwide's global AI strategy, aligning … company's AAP/EEO goals and policies. Perform other duties as required/assigned by manager. Knowledge, Skills, & Abilities Required Bachelor's degree in computer science, AI, Machine Learning, Data Science, or a related field (Master's degree + work experience preferred). 7+ years of experience in data science, Machine Learning, or AI, with at least More ❯

research that will help our customers imagine, design, and make a better world.We are a team of scientists, researchers, engineers, and designers working together on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.This role will report to a Research Manager in the AI Lab. Responsibilities … A Master's or PhD in a field related to AI/ML, such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, or related disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning … coding abilities in Python Strong Software development skills and familiarity with GPUs, MLOps, Git, High-performance large-scale ML systems and platforms. Experience with Transformers, LLMs, NLP, Multi-modal Deep Learning, and VLMs/MLLMs Publication track record in machine learning conferences and/or journals Preferred Qualifications Significant post-graduate research experience, or five or more More ❯

present tailored AI solutions with real-world impact, not just slideware. Build trust with clients through proof of value and live examples of implemented solutions. Required Technical Skills Machine Learning , Deep Learning , Natural Language Processing , Computer Vision , Generative AI , Reinforcement Learning , LLMs (e.g., GPT, Claude, Mistral, LLaMA, DeepSeek, etc.). Agent-based architectures , RAG , prompt engineering More ❯

present tailored AI solutions with real-world impact, not just slideware. Build trust with clients through proof of value and live examples of implemented solutions. Required Technical Skills Machine Learning , Deep Learning , Natural Language Processing , Computer Vision , Generative AI , Reinforcement Learning , LLMs (e.g., GPT, Claude, Mistral, LLaMA, DeepSeek, etc.). Agent-based architectures , RAG , prompt engineering More ❯

predictive analytics and insights across all brands and channels. You'll develop recommendation systems and predictive models that support global marketing and CRM strategies. Responsibilities Lead development of machine learning solutions for CRM personalisation Build and optimise recommendation engines using neural networks and deep learning Collaborate with CRM and regional marketing teams to align with campaign goals … and segmentation strategies Partner with engineering and data teams to ensure scalable solutions Monitor and improve model performance using data insights and feedback Requirements Proven experience in machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas More ❯

predictive analytics and insights across all brands and channels. You'll develop recommendation systems and predictive models that support global marketing and CRM strategies. Responsibilities Lead development of machine learning solutions for CRM personalisation Build and optimise recommendation engines using neural networks and deep learning Collaborate with CRM and regional marketing teams to align with campaign goals … and segmentation strategies Partner with engineering and data teams to ensure scalable solutions Monitor and improve model performance using data insights and feedback Requirements Proven experience in machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas More ❯

predictive analytics and insights across all brands and channels. You'll develop recommendation systems and predictive models that support global marketing and CRM strategies. Responsibilities Lead development of machine learning solutions for CRM personalisation Build and optimise recommendation engines using neural networks and deep learning Collaborate with CRM and regional marketing teams to align with campaign goals … and segmentation strategies Partner with engineering and data teams to ensure scalable solutions Monitor and improve model performance using data insights and feedback Qualifications Proven experience in machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas More ❯

x Senior Data Scientists | London | Financial Services 📍 London (Hybrid) 💰 Up to £100,000 + Equity + Private Health 🧑 💻 Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI Our client partners with some of the world’s leading financial institutions to deliver innovative, data-driven solutions that transform decision-making and operational performance. From major banks and asset … managers to insurers and fintech disruptors, they help their clients harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly evolving industry. *If you’re looking for an opportunity to shape the future of applied AI in this sector, this is your chance.* ROLE: Senior Data Scientist We’re looking for 3 x … ready AI. You’ll also act as a trusted advisor to clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning More ❯

x Senior Data Scientists | London | Financial Services 📍 London (Hybrid) 💰 Up to £100,000 + Equity + Private Health 🧑 💻 Machine Learning | Data Science Libraries | Deep Learning Frameworks | AI Our client partners with some of the world’s leading financial institutions to deliver innovative, data-driven solutions that transform decision-making and operational performance. From major banks and asset … managers to insurers and fintech disruptors, they help their clients harness the power of advanced analytics, machine learning, and AI to stay competitive in a rapidly evolving industry. *If you’re looking for an opportunity to shape the future of applied AI in this sector, this is your chance.* ROLE: Senior Data Scientist We’re looking for 3 x … ready AI. You’ll also act as a trusted advisor to clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning More ❯

products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers … and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model … design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What More ❯

products, content and services millions of people love. And we do it all right here at Sky. What you'll do We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low-latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers … and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform. Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model … design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs. Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems. What More ❯