1 to 25 of 35 Permanent Amazon SageMaker Jobs in the UK excluding London

develop, test, and support production-ready models using modern cloud technologies. The Role You will work primarily with Python, SQL, and AWS (including Amazon SageMaker) to: Extract, transform, and analyse data from AWS data platforms Perform exploratory data analysis and communicate insights clearly Build and evaluate baseline machine … learning models (classification & regression) Support model experimentation in Amazon SageMaker Unified Studio Contribute to model deployment, monitoring, and safe rollout practices Follow best practices in Git, code review, testing, and Agile delivery Support data governance, documentation, and privacy-by-design principles This role offers structured mentorship and exposure ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible AI Frameworks ...

related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/Airflow/Beam) Mobile and front-end web application development experience What We Offer ...

related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/Airflow/Beam) Mobile and front-end web application development experience What We Offer ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...