17 of 17 Permanent Keras Jobs in England

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and More ❯

Previous experience developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it More ❯

experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI/CD, containerization (e.g. More ❯

warehouses Experience building classification models (binary, multi-class, anomaly detection) Familiarity with unsupervised learning algorithms such as K-Means and DBSCAN Hands-on experience with scikit-learn, TensorFlow, PyTorch, Keras, OpenCV Deep expertise in Google Cloud Platform (GCP), including BigQuery, Vertex AI, and AlloyDB Familiarity with Docker and Kubernetes Soft Skills and Behaviours Strong communicator across technical and non-technical More ❯

have tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processingHands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras)Knowledge of CNN architectures and training dynamicsProven experience deploying and optimizing models for real-time applicationsStrong data science and metrics literacy Nice to have: PhD or Master's in Computer More ❯

tangible, high-profile impact. Essential experience: Strong background in Computer Vision and image/video processing Hands-on experience with OpenCV pipelines Proficiency with deep learning frameworks (PyTorch, TensorFlow, Keras) Knowledge of CNN architectures and training dynamics Proven experience deploying and optimizing models for real-time applications Strong data science and metrics literacy Nice to have: PhD or Master's More ❯

scikit-learn , and Jupyter Notebooks Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

scikit-learn , and Jupyter Notebooks Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability More ❯

stere, SLAM or Depth estimation from video Proficient in Linux Experience with Docker Experience with large-scale data sets Proficient with open source machine learning platforms such PyTorch or Keras/tensorflow. Ability to develop using rapid prototyping techniques aimed at demonstrating applications quickly in a fast moving environment. Agile/DevOps Familiarity f SCRUM Familiarity f DevOps Continuous Integration More ❯

Learn : Strong desire to learn new technologies and methodologies. Teamwork : Ability to collaborate with others and contribute to team success. Preferred Qualifications : Experience with machine learning frameworks (e.g., TensorFlow, Keras, PyTorch). Understanding of data structures, algorithms, and mathematical foundations for AI. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) is a plus. Previous internship or project experience in More ❯

AI methods and apply them where appropriate to advance our product capabilities 🔧 Your Background Essential: Solid software engineering background with Python and deep learning frameworks (e.g. PyTorch, TensorFlow, or Keras) Experience delivering computer vision solutions, ideally involving scientific or microscopy images Strong grasp of convolutional neural networks (CNNs) and modern AI techniques Familiarity with Git-based workflows and modern DevOps More ❯

software engineering and algorithm development skills in Python, including advanced image processing for 3D datasets, and ideally interpretation of biological (not medical) data from time series microscopy. Likely TensorFlow, Keras, PyLattice or similar. Ideally use of machine learning, neural networks, particularly CNNs given the data involved, feature extraction and tracking. Familiarity with computer vision, cellular imaging, volumetric tiling, voxel imaging More ❯