26 to 50 of 133 Deep Learning Jobs in London

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 ❯

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 ❯

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 ❯

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 ❯

RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with our recruitment team More ❯

RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning, deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and … clear and accessible manner. Qualifications: Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous - desirable Professional accounting qualification preferred, however not a requirement - desirable To discuss this or wider Technology roles with our recruitment team More ❯

products, content and services millions of people love. And we do it all right here at Sky. What you'll be doing 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 … 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 … you'll bring Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe). Experience with high More ❯

London, UK This is a permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are … RL, LLMs, and generative modelling, helping us build the next generation of foundation models Responsibilities: Develop and refine RLHF algorithms for large language and generative models. Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment. Train, fine-tune, and evaluate LLMs and diffusion models at scale. Design experiments to … and human feedback teams to build scalable alignment pipelines. Publish findings in top-tier AI conferences and contribute to open-source frameworks. Key Requirements: PhD in Computer Science, Machine Learning, or related field. Publications at NeurIPS, ICML, ICLR, ACL, or related venues. Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training More ❯

London, UK This is a permanent position with candidates required to do hybrid working in either Cambridge or London. Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are … RL, LLMs, and generative modelling, helping us build the next generation of foundation models Responsibilities: Develop and refine RLHF algorithms for large language and generative models. Research and implement deep reinforcement learning methods (policy gradients, actor-critic, off-policy learning) for model alignment. Train, fine-tune, and evaluate LLMs and diffusion models at scale. Design experiments to … and human feedback teams to build scalable alignment pipelines. Publish findings in top-tier AI conferences and contribute to open-source frameworks. Key Requirements: PhD in Computer Science, Machine Learning, or related field. Publications at NeurIPS, ICML, ICLR, ACL, or related venues. Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training More ❯

Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial A FTSE 100 retail client are on the look for a Machine Learning Engineer to join their data science function to drive cutting-edge ML technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Machine … Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc. … as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI, GCP Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications More ❯

Job Description Role Overview: Apply cutting-edge AI and deep learning methods to communication system challenges. Contribute to high-impact research with opportunities to publish at leading AI or communication venues (NeurIPS, IEEE, etc.). Collaborate closely with our top Cambridge-based researchers and international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in … Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM and MIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication and teamwork skills. Enthusiasm for innovative research with real-world impact. Join us to More ❯

Job Description Role Overview: Apply cutting-edge AI and deep learning methods to communication system challenges. Contribute to high-impact research with opportunities to publish at leading AI or communication venues (NeurIPS, IEEE, etc.). Collaborate closely with our top Cambridge-based researchers and international colleagues. Requirement Preferred Qualifications Currently pursuing (or recently completed) a PhD, preferably in … Electrical Engineering or related quantitative fields. Background in wireless communication systems, e.g., OFDM and MIMO technologies. Track record of related publications or successful projects. Proficiency in Deep Learning frameworks (PyTorch, JAX). Familiarity with advanced AI methods (e.g., transformer models). Excellent scientific communication and teamwork skills. Enthusiasm for innovative research with real-world impact. Join us to More ❯

technology and analytics team , working alongside experienced engineers, data scientists, and AI specialists shaping the future of intelligent finance. In this role, you’ll: 🧠 Develop, train, and optimise machine learning and deep learning models for real-world applications ⚙ Build and support AI pipelines — from data preprocessing to model deployment and monitoring 💬 Collaborate with cross-functional teams to … frameworks such as PyTorch, TensorFlow, and Hugging Face 🔒 Contribute to model governance, compliance, and responsible AI practices What’s in it for you? 📈 Career Growth – Gain structured mentorship, ongoing learning opportunities, and exposure to cutting-edge AI technologies. 💡 Innovation Culture – Work in a collaborative environment that values experimentation, curiosity, and real-world impact. 🏢 Hybrid Flexibility – Enjoy a balance of … What We’re Looking For: 🎓 Degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field (Master’s preferred) 💼 Some proven industry experience applying AI or machine learning (internship, placement, or full-time role) 🐍 Strong programming skills in Python and familiarity with frameworks such as TensorFlow , PyTorch , or scikit-learn 📊 Understanding of machine learning algorithms, data More ❯