16 of 16 Keras Jobs in the UK

solutions, with a strong focus on Microsoft Azure. • Proficiency in Python and experience with relevant AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras). • Demonstrated experience with Azure Machine Learning, including MLOps concepts, model registration, deployment (AKS, ACI), and monitoring. • Hands-on experience with Azure data services such ...

solutions, with a strong focus on Microsoft Azure. • Proficiency in Python and experience with relevant AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras). • Demonstrated experience with Azure Machine Learning, including MLOps concepts, model registration, deployment (AKS, ACI), and monitoring. • Hands-on experience with Azure data services such ...

join our growing teams. Key Responsibilities 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 ...

Azure) and modern DevOps practices (Infrastructure-as-Code). Proficiency with Git, Unix/Linux, Docker. Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn (commercial experience not essential). Excellent communication skills for both internal and client-facing interactions. Awareness of MLOps is a plus. ...

Azure) and modern DevOps practices (Infrastructure-as-Code). Proficiency with Git, Unix/Linux, Docker. Familiarity with ML frameworks such as TensorFlow, PyTorch, Keras, or scikit-learn (commercial experience not essential). Excellent communication skills for both internal and client-facing interactions. Awareness of MLOps is a plus. ...

indispensable Cloud experience in one of AWS - Amazon Web Service, Azure, Google Cloud Platform Proficiency oinn Machine Learning libraries and frameworks like Tensorflow, Keras, Pytorch, OpenCV, Bertl, Elmo SpaCy, NLTK, etc. Preferred- Experience creating Chatbots, and similar applications that use NLP. Object Character Recognition and Computer Vision projects like Face ...

design to validation, deployment, and monitoring. Technical Proficiency: Fluency in Python, SQL, or similar languages, and experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version control. Cloud Platforms: Exposure to Azure ...

design to validation, deployment, and monitoring. Technical Proficiency: Fluency in Python, SQL, or similar languages, and experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version control. Cloud Platforms: Exposure to Azure ...

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 ...

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 ...

reliable results. True ML Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch ...

reliable results. True ML Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch ...

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 ...

Forest, Gradient Boosted Trees, XGBoost Unsupervised Models: K-Means, DBSCAN, Hierarchical Clustering Deep Learning ANN, CNN, RNN, LSTM Frameworks: TensorFlow (Gradient Tape), PyTorch NN, Keras Sequential NLP & Generative AINLTK, CBoW, n-grams, Word2Vec, TF-IDF, Word Embeddings Transformers: BERT, ELMo OpenAI Models: GPT-3.5 Turbo, GPT-4o, GPT-3o Reasoning … text-embedding-ada-002 Libraries & Tools numpy, pandas, scipy, scikit-learn, tensorflow, keras, nltk, matplotlib, seaborn, plotly Programming Languages Python, R, C++, C#, Java, Node.js, HTML, SQL Agentic AI OpenAI Agents SDK, Model Context Protocol (MCP), LangChain, LangGraph, Bedrock Agents, CrewAI, Helicone Rate:400GBP/day Inside IR35 Work mode ...

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 … 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 ...

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 … 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 ...