26 to 28 of 28 Amazon SageMaker Jobs in London

best practices for AI/ML implementation and data analysis. Job Requirements: Advanced proficiency in Machine Learning and Data Science. Intermediate proficiency in Amazon Sagemaker. Experience with Retrieval-Augmented Generation, Software Development Life Cycle, and Model Context Protocol. Strong problem-solving skills and the ability to contribute ...

Core Capabilities Enterprise AI & Architecture Agentic AI, RAG, enterprise ML in regulated FS Azure AI Studio, Azure AI Search, Fabric, Document Intelligence AWS Bedrock & SageMaker pattern experience FastAPI, Kubernetes, Docker, CI/CD (ADO/GitHub/GitLab) Secure landing zones, policy-driven cloud governance, FinOps Vector, Data & Integration … Azure-native sources to enable analytics and GenAI readiness. Cross-Cloud FS AI Enablement Led design patterns portable across Azure + AWS Bedrock/SageMaker for regulated workloads. Developed controls for data boundary enforcement & model validation pipelines. GenAI & Cloud Solutions Architect Accelerated AI value from PoC pilot scaled capability ...

machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration skills, and a results-driven mindset Role responsibilities: Build … tune, and maintain predictive and ML models using AWS SageMaker Analyse large datasets and perform feature engineering to improve model performance Run experiments, test hypotheses, and optimise models for accuracy and value Monitor model performance and manage retraining over time Collaborate with Data Engineers, BI Developers, and Analysts ...