1 to 25 of 53 Remote Deep Learning Jobs in London

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Type: Contract (6 months, with extension likely) Start Date: Immediate/Within 2-4 weeks Job Description: We are seeking an experienced and highly motivated Lead Software Engineer with deep expertise in Artificial Intelligence (AI) , Machine Learning (ML) , and Python development to lead the design, development, and deployment of intelligent systems and data-driven applications for a leading … with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc. More ❯

expertise in AI and data science with proven leadership in delivering enterprise-grade AI systems to public and private sector clients. Key Responsibilities Design and architect AI and machine learning solutions across a range of use cases, including predictive analytics, natural language processing, and generative AI. Lead technical delivery teams, providing guidance on best practice, architecture, and development processes. … Contribute to business development activities, including bid writing, client presentations, and proposal delivery. Skills and Experience Required Strong capabilities across a range of AI techniques, including supervised and unsupervised learning, generative AI, deep learning, graph analytics, statistical modelling, time-series forecasting, geospatial analysis, NLP, sentiment analysis, and pattern detection. Excellent communication skills, with the ability to present … within large organisations) through RFI/RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using cloud provisioning tools such as Terraform More ❯

expertise in AI and data science with proven leadership in delivering enterprise-grade AI systems to public and private sector clients. Key Responsibilities Design and architect AI and machine learning solutions across a range of use cases, including predictive analytics, natural language processing, and generative AI. Lead technical delivery teams, providing guidance on best practice, architecture, and development processes. … Contribute to business development activities, including bid writing, client presentations, and proposal delivery. Skills and Experience Required Strong capabilities across a range of AI techniques, including supervised and unsupervised learning, generative AI, deep learning, graph analytics, statistical modelling, time-series forecasting, geospatial analysis, NLP, sentiment analysis, and pattern detection. Excellent communication skills, with the ability to present … within large organisations) through RFI/RFP responses, bid documentation, and client presentations. Hands-on experience with data science platforms such as Databricks , Dataiku , AzureML , or SageMaker , and machine learning frameworks such as TensorFlow , Keras , PyTorch , and scikit-learn . Expertise in cloud platforms ( AWS , Azure , Google Cloud ) and experience deploying solutions using cloud provisioning tools such as Terraform More ❯

Machine Learning/Data Engineer £700-750/day overall assignment rate to umbrella Fully remote 3-6 month initial Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth. With 40% of sales from sustainable products, this is a company … that combines scale, innovation and purpose. As a Machine Learning Engineer, you'll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows and ML issues in live production environments. We're looking … for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong More ❯