26 to 32 of 32 Keras Jobs in the UK

presales, client partner, or solution principal role.Experience supporting sales forecasting, pipeline management, deal structuring, and sales coaching.Familiarity with AI/ML and Data Management frameworks and tools (TensorFlow, PyTorch, Keras, Spark, Databricks etc.)Experience in on-premise data center infrastructures relevant to AI/ML, Data and Data ManagementStrong cross-functional leadership and internal stakeholder management skills.Exceptional presentation, proposal development 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 ❯

skills, a quick learning ability, and enthusiasm for tackling complex challenges. You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras . You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders. Accommodation requests If you need More ❯

with AI systems, machine learning models, or related technologies using Microsoft AI tools and Azure. Technical Skills Needed Familiarity with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras). Experience in Microsoft Azure as well as Microsoft AI tools (Copilot) is a must. Proficient in programming languages such as Python, Java, or C++. Understanding of system architecture and More ❯

LLM features in a regulated environment with sensitive data. You’ll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you’ll do Research, prototype, and deploy LLM use cases … Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you’ll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark More ❯

team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using … problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using More ❯

team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using … problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using More ❯