1 to 25 of 171 Neural Network Jobs in England

and experimentation. You’ll work within multidisciplinary teams to develop, validate and deploy machine learning models to meet challenging customer requirements. Key Responsibilities Develop and train neural network models using frameworks such as PyTorch and TensorFlow Select and adapt model architectures to meet specific project requirements Build, curate, and manage training datasets, including data augmentation, feature extraction … technical and non-technical audiences Requirements Degree in Computer Science, Engineering, Mathematics, or related field Strong development skills in Python and C/C++ Experience with neural network architectures including RNNs, transformers, and vector quantisation In-depth knowledge of machine learning architectures and training algorithms Experience in model training, quantisation, and conversion for inference Hands-on experience More ❯

data Translate complex business needs into thoughtful, practical data products that support better decision-making Apply a wide toolkit of methods from classical statistics and regression models to neural networks, ensemble methods, and AI techniques, to answer important business questions Share insights through clear, compelling storytelling, dashboards, and visualisations that empower senior stakeholders to act with confidence Coach More ❯

for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis for handling time-dependant data. Deep learning and neural networks. LLM Operations Expertise in managing and operationalising large language models. Experience in deploying models on cloud platforms (e.g. AWS, Sage maker, Google AI Platform, IBM Watson) IND_PC3 More ❯

on technical tasks. Familiarity with Agile methodologies and experience working in Agile teams. Key Technical Skills Python (Flask/FastAPI, OOP, unit testing). Machine learning model experience (Neural networks, Random forests etc.). Terraform or similar Infrastructure as Code (IaC) tools. GCP, AWS, or Azure. Docker and containerised deployments. CI/CD pipelines. Git based development. SQL. More ❯

Translating complex business needs into thoughtful, practical data products that support fairer and more innovative pricing approaches Applying a wide toolkit of methods - from time-series modelling to neural networks - to answer important business questions Sharing insights in clear, compelling ways that empower senior decision-makers to act confidently Coaching and encouraging junior data scientists, creating space for More ❯

area of the business within a growing team What else is involved? Architect & Build: Design, test and deploy state-of-the-art predictive models (e.g. Two-Tower, Recurrent Neural Networks, XGBRanker) that drive the internal Ad ranking and assignment algorithms. Optimise Feedback Loops: Increase responsiveness of ad algorithms to real-world events and outcomes in the pursuit of More ❯

or streamlining and automating data refresh processes. What you'll be working on Building and improving price optimisation machine learning pipelines including data validation, classification, clustering, predictive modelling, neural networks, statistical model evaluation, optimisation, and process automation. Preparing presentations for clients based on data and market insights Interacting with clients on a regular basis and providing pricing guidance More ❯

data visualisation skills using tools like Tableau, Spotfire, Power BI etc. Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering/random forest (desirable). Tech Stack: SQL, Python, R, Tableau, AWS Athena + More! More information: Enjoy fantastic More ❯

self-taught AI/ML practitioner with relevant projects An early-career technologist seeking formal qualifications and impactful work Essential skills: Strong foundation in AI/ML (e.g. neural networks, NLP, transformers) Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow) Familiarity with LLM APIs and open-source models (e.g. GPT, Claude, Whisper) Understanding of agentic AI frameworks More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯

React) and backend (e.g. Node.js) development Machine Learning & Artificial Intelligence Machine Learning (General concepts, model development, experimentation, training, evaluation) Deep Learning (General, frameworks like TensorFlow, PyTorch, JAX, Keras, neural networks, CNNs, RNNs, transformer architecture, LSTM) Natural Language Processing (NLP) Reinforcement Learning (e.g., PPO, Q-learning, policy gradients, A2C, DQN, AlphaZero) Computer Vision (e.g., image processing, analysis, instance segmentation More ❯