1 to 25 of 103 Neural Network Jobs in the UK

to extract knowledge or insights to drive the future of artificial intelligence. What you will be doing: Applying and/or developing statistical modelling techniques (such as deep neural networks, Bayesian models, Generative AI, Forecasting), optimization methods and other ML techniques Converting data into practical insights Analysing and investigating data quality for identified data and communicate it to More ❯

including AI/Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow More ❯

an experienced AI/ML Engineer to help enterprise clients accelerate their adoption of advanced machine learning technologies. This role will focus on building graph-based neural network (GNN) models, generating ScaNN-based embeddings, and training scalable ML models for search, recommendation, and classification systems. You will collaborate closely with Google Cloud engineers, architects, and data scientists … to deliver innovative, production-ready AI solutions. Key Responsibilities Design and implement Graph Neural Network (GNN) architectures for enterprise-scale applications. Develop and optimize vector embedding generation pipelines using ScaNN or similar ANN techniques. Train, fine-tune, and deploy ML/DL models using TensorFlow, PyTorch, JAX, or similar frameworks. Collaborate with data engineers and solution architects … facing experience of discovery, assessment, execution, and operations. Demonstrated excellent communication, presentation, and problem solving skills. Experience in project governance and enterprise customer management. Proficiency in building Graph Neural Networks (GNNs) using frameworks like DGL, PyTorch Geometric, or similar. Experience with ScaNN or other approximate nearest neighbor (ANN) techniques for vector similarity search. Hands-on experience with Google More ❯

and differential privacy methods Familiarity with next-generation computing paradigms such as neuromorphic computing, brain-inspired architectures, or quantum machine learning Specialized knowledge in computational linguistics or graph neural networks for complex relational data Contributions to open-source machine learning projects or frameworks Please note: This role focuses on fundamental research that pushes beyond current AI paradigms to More ❯

and probabilistic representations for diverse ML tasks. Build and optimize tools for scalable probabilistic inference under memory, latency, and compute constraints. Apply and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct More ❯

With access to 170m+ people in over 100 global markets, we offer unrivalled global reach with local relevancy. Validated by industry leading anti-fraud technology, Kantar's Profiles Audience Network delivers the most meaningful data with consistency, accuracy, and accountability - all at speed and scale. We're the world's leading data, insights, and consulting company; we shape the … of Kantar might I be joining? You'll be joining our Profiles division, home to specialists in survey design, sampling and data science. With the world's largest audience network (over 170 million people), we're trusted by many of the worlds leading brands to provide amazing insights from real people. We shape the brands of tomorrow by better … With access to 170m+ people in over 100 global markets, we offer unrivalled global reach with local relevancy. Validated by industry leading anti-fraud technology, Kantar's Profiles Audience Network delivers the most meaningful data with consistency, accuracy, and accountability - all at speed and scale. Job Details We're the world's leading data, insights, and consulting company; we More ❯

continually expand knowledge and test new technologies. Ideal Skills & Capabilities Deep understanding of artificial intelligence and machine learning techniques: Proficiency in supervised/unsupervised/semi-supervised learning, neural networks, SVM, tree-based methods, and NLP. Expertise in generative AI tools: Experience with prompt-engineering, fine-tuning language models, and selecting the right models for various tasks. Proficiency More ❯

such as Python, R, or Java. Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn. Machine Learning Knowledge: Strong understanding of machine learning algorithms, neural networks, and deep learning techniques. Analytical Skills: Excellent analytical and problem-solving skills, with the ability to work with complex datasets. Communication Skills: Strong written and verbal communication skills More ❯

A degree in Artificial Intelligence, Data Science, Computer Science, Mathematics, or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world More ❯

A degree in Artificial Intelligence, Data Science, Computer Science, Mathematics, or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt). Strong foundational knowledge of machine learning and deep learning algorithms, including deep neural networks, supervised/unsupervised learning, predictive analysis, and forecasting. Expert-level proficiency in Python, with a demonstrated ability to develop and debug production-grade code. Desired Skills (Bonus Points More ❯

engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms. Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production. Excellent problem-solving skills, with a passion for More ❯

engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms. • Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production. • Excellent problem-solving skills, with a passion for More ❯

engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms. • Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production. • Excellent problem-solving skills, with a passion for More ❯

engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms. • Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production. • Excellent problem-solving skills, with a passion for More ❯

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 Development of neural networks Implementing and maintaining MLops workflows Work alongside Data Engineers and DevOps Engineers to ensure continuous integration and deployment of machine learning models in production. Proactive learning and researching … Computer Science, Physics, Mathematics, Artificial Intelligence) is preferable Proven track record of successfully completing AI projects that deliver tangible business results Experienced writing production level code Experience developing neural networks into production Experience with Docker Experience with NLP and/or computer vision Exposure to cloud technologies (eg. AWS and Azure) Exposure to Big data technologies Exposure to … leave days per year Pension: Award winning pension scheme (up to 10% employer contribution) Wellbeing: Employee Assistance Programme with access to free mental health support, financial wellbeing support and network groups to demonstrate our ongoing commitment to diversity & inclusion (Enable, Pride, Equalise, Reservists, Carers) Lifestyle: Discounted Gym membership, Cycle to work scheme Training: Free access to more than More ❯

to experience) Good background in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.) Familiarity with PyTorch , TensorFlow , JAX or similar frameworks Strong coding abilities in Python and/or C++ Preferred Qualifications … Generative AI Reinforcement Learning LLMs and Natural Language Processing Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry , discrete geometry , functional mapping, geometric deep learning, graph neural networks) Multi-modal deep learning and/or information retrieval Architecture, Construction, Manufacturing, Media & Entertainment or other Autodesk domains Salary transparency: Salary is one part of Autodesk's competitive More ❯

to experience) Good background in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.) Familiarity with PyTorch , TensorFlow , JAX or similar frameworks Strong coding abilities in Python and/or C++ Preferred Qualifications … Generative AI Reinforcement Learning LLMs and Natural Language Processing Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry , discrete geometry , functional mapping, geometric deep learning, graph neural networks) Multi-modal deep learning and/or information retrieval Architecture, Construction, Manufacturing, Media & Entertainment or other Autodesk domains Learn More About Autodesk Welcome to Autodesk! Amazing things are More ❯

science concepts to non-technical stakeholders. Key Responsibilities 1. Advanced Predictive Models: Utilize machine learning algorithms to analyze historical data and identify patterns. Models such as regression analysis, neural networks, or ensemble methods can predict ETAs more accurately by considering various factors like traffic conditions, weather, route efficiency, and historical performance. 2. Real-Time Data Integration: Incorporate real More ❯

world problems; Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar; Experience with multi-GPU and distributed training at scale More ❯

ideally working with data engineering. Proficiency in statistical analysis, machine learning, and data mining techniques. A good understanding of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and More ❯

via APIs Familiarity with data visualization tools Knowledge of locating, assessing and integrating third party data-sets Experience with machine learning techniques and libraries (e.g., regression, classification, clustering, neural networks). Solid understanding of AI concepts, including supervised and unsupervised learning. Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure) Education and Knowledge Bachelor's or Master's More ❯

II, Machine Learning (ThousandEyes) Location: London, United Kingdom Who We Are Cisco ThousandEyes is a Digital Experience Assurance platform that empowers organizations to deliver flawless digital experiences across every network - even the ones they don't own. Powered by AI and an unmatched set of cloud, internet, and enterprise network telemetry data, ThousandEyes enables IT teams to proactively … in building and evaluating ML models and delivering large-scale ML products. MS or PhD in a relevant field. Proficient in crafting machine learning models, your expertise spans neural networks including transformer models, Large Language Models, decision trees, and other traditional machine learning models, translating conceptual ideas into actual solutions. Fluent in some of these machine learning frameworks More ❯

field; or Master’s degree with 2+ years of relevant industry experience; or Bachelor’s degree with 4+ years of relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (GANs, diffusion models). Practical experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow). Advanced programming skills in Python . Strong problem-solving, analytical More ❯