15 of 15 Keras Jobs in the UK

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 ❯

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 ❯

science, engineering, or computer science - Experience communicating across technical and non-technical audiences - Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet - Fluency in written and spoken English Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting More ❯

and PyTorch. Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, TensorFlow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure 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 ❯

regulated environment: medical, aerospace, or automotive Experience of real-time operating systems and embedded development Experience working to an Agile lifecycle. Awareness of machine-learning frameworks such as Pytorch, Keras/Tensorflow, MATLAB Machine Learning toolbox Awareness of mathematical libraries used for signal processing, image processing and data processing Awareness of high-performance computing and the challenges of parallel processing 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 ❯