1 to 25 of 78 Remote Deep Learning Jobs in the UK

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid We are seeking an Engineering Manager to join our Applied Machine Learning team , focused on delivering innovative experiences and insights for coaches, athletes, and fans. This role leads high-impact initiatives using advanced computer vision and deep learning technologies at scale—powering … on experience in building, maintaining, and monitoring complex AI/ML systems operating in production at scale. Technical Proficiency : Strong experience in several of the following domains: Classical and deep learning-based computer vision Multi-view geometry GPU-accelerated computing Edge inference Large language models (LLMs) Real-time systems Signal processing Excellent Communication : Ability to explain complex technical … professional life, including generous vacation policies, company holidays, meeting-free days, and remote work options. Autonomy and Ownership : A culture that encourages individual ownership, open communication, and innovation. Continuous Learning : Access to career development resources, professional growth opportunities, and internal mentorship. Optimized Work Environment : Supportive, well-equipped workspaces—whether remote or in-office—designed to help you do your More ❯

position offers a unique opportunity to drive groundbreaking research and development in state-of-the-art NLP models and applications, impacting a global user base. The role requires a deep theoretical understanding and practical expertise in machine learning, deep learning, and advanced NLP techniques. You will be instrumental in shaping the future of how humans interact … technology through intelligent language understanding and generation. Responsibilities Lead the research and development of novel NLP algorithms and models, pushing the boundaries of artificial intelligence. Design and implement advanced deep learning architectures for tasks such as text generation, summarization, sentiment analysis, and machine translation. Conduct cutting-edge research in areas like transformer models, large language models (LLMs), and … and contribute to the scientific growth of the team. Develop and maintain high-quality, production-ready code for AI models. Stay abreast of the latest advancements in NLP, machine learning, and deep learning. Contribute to the strategic direction of the company's AI research roadmap. Evaluate and benchmark new models and techniques against industry standards. Qualifications Ph.D. in More ❯

Research Team, working at the forefront of generative AI and its applications in life sciences. Our team is dedicated to building foundational expertise and developing the next generation of deep learning technologies. Roles are available for both recent graduates and senior profiles. Generative foundation models like ESM-3 1 , AlphaFold 2 , RFDiffusion 3 , ProteinMPNN 4 are revolutionising computational … Develop Biological Foundation Models Contribute to the creation of new models that push the boundaries of what's possible in computational biology. Collaborate Across Disciplines Work closely with Machine Learning Engineers, Research Engineers, Computational Biologists, and other experts. Leverage Cutting-Edge Resources Utilise our near-exascale supercomputing cluster, Kyber 9 , to conduct large-scale training and evaluation of generative … models. Publish and Present Research Share your findings at top-tier conferences and in leading journals. Responsibilities Innovate in Deep Learning Research Develop and implement novel research on multimodal generative foundation models and their biological applications. Contribute to Team Success Collaborate with team members to achieve research goals and contribute to a supportive, knowledge-sharing environment. Engage in More ❯

seeking Applied Research Scientists with expertise in RNA modeling, RNA optimization, or RNA design to join our world-class, multi-disciplinary team. This role sits at the intersection of deep scientific research and practical product development, aimed at building cutting-edge biological AI models and deploying them to researchers advancing the life sciences. Applied Research Scientists at InstaDeep leverage … their deep expertise in scientific principles, artificial intelligence, and computational biology to create more accurate, efficient, and scalable tools that enhance our understanding of biology and accelerate the development of medical treatments, including RNA therapeutics. This position demands close collaboration across AI research, biology, engineering, and business teams, as well as with strategic partners like BioNTech. Success in this … design, optimisation and modelling. Design, implement, and evaluate proof-of-concept methods and benchmarking experiments using state-of-the-art approaches. Leverage both classical computational biology tools and modern deep learning approaches for tasks such as RNA design, optimization, and molecular modeling. Enhance the understanding of AI model behavior in biological applications by contributing to interpretability and performance More ❯

quality, model performance, evaluation, failure modes, and how AI fits into real financial workflows within a modern fintech platform. What You’ll Be Doing: Designing, training, and deploying machine learning and deep learning models for financial analytics, credit/risk scoring, and portfolio insights Building LLM-powered tools (e.g. using GPT-class models) that assist with data … of models in financial contexts What We’re Looking For: A completed AI-focused Master’s degree from a top-tier university such as: MSc Artificial Intelligence, MSc Machine Learning, MSc Data Science with a strong AI/ML track. Or a closely related programme with substantial AI/ML content Strong applied project experience in machine learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using More ❯

quality, model performance, evaluation, failure modes, and how AI fits into real financial workflows within a modern fintech platform. What You’ll Be Doing: Designing, training, and deploying machine learning and deep learning models for financial analytics, credit/risk scoring, and portfolio insights Building LLM-powered tools (e.g. using GPT-class models) that assist with data … of models in financial contexts What We’re Looking For: A completed AI-focused Master’s degree from a top-tier university such as: MSc Artificial Intelligence, MSc Machine Learning, MSc Data Science with a strong AI/ML track. Or a closely related programme with substantial AI/ML content Strong applied project experience in machine learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using More ❯

and the other dedicated to fundamental research that supports both our applications and the broader scientific community. Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Responsibilities:- Contribute to ongoing research in machine learning and artificial intelligence Help develop and implement algorithms Collaborate with researchers … preparing publications and technical reports Stay up to date with the latest advancements in AI and related fields Requirement Qualifications Required: Currently enrolled in a PhD program in Machine Learning, Artificial Intelligence, Mathematics, Computer Science, Physics, or a related field Strong interest in research and a background in machine learning or a related area Experience with programming languages … similar Strong problem-solving skills and ability to work independently and collaboratively Good communication skills and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands More ❯

world. Data Analytics & AI - Data Science & AI - Senior Consultant EY exists to build a better working world. We empower our people by offering the culture, tech, teams, scale, challenges, learning, and the relationships for you to personalise and build your career, helping to create long-term value for clients, people and society and build trust in the capital markets. … anomalies that can inform business strategies. Statistical Modeling : The ability to applying statistical techniques to extract insights, build predictive models, interpret data, and support data driven decision making. Machine Learning and AI Model End to End Management : The ability to build and manage the full lifecycle of ML models including development, validation, deployment, and monitoring in production environments. Collaboration … The ability to work closely with cross-functional teams to develop, test, and deploy advanced machine learning models, ensuring alignment with business objectives and seamless integration into client operations. Communication : The skill to effectively communicate complex analytical findings and model results to stakeholders, translating data-driven insights into business language that informs decision-making. Continuous Learning : The ability More ❯

Machine Learning Engineer (LLM/AI Systems) London/Hybrid | 0–3 Years Experience | Competitive Salary Are you obsessed with AI and large language models? We’re an early-stage startup building real-world products powered by LLMs — from intelligent copilots to adaptive automation tools — and we’re looking for curious minds to help us shape the future of … edge of ML/AI research — we give you time and resources to explore, learn, and publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector … Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and shape the product roadmap. An environment that values learning, creativity, and personal growth over bureaucracy. Perfect For Graduates or junior engineers with a passion for AI/ML looking to break into applied LLM engineering. Researchers or data 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯