8 of 8 Amazon SageMaker Jobs in the North West

delivery of a production-grade machine learning platform on AWS. What you’ll be doing Design and maintain a production MLOps platform on Amazon SageMaker (Studio, Training, Pipelines, Endpoints) — including model registry, automated retraining, drift monitoring, and governance gates Lead the migration of a 12-model production suite … e.g., the CVM suite) from legacy infrastructure to SageMaker, owning parity testing methodology and sign-off Build and maintain CI/CD pipelines (CodePipeline/CodeBuild or equivalent) for automated model promotion across environments Define and enforce IAM least-privilege policies, KMS key management, and VPC/PrivateLink network ...

containerization technologies like docker, Kubernetes, AWS EKS etc.Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc.Master's degree or above in Machine learning/data science, computer science, applied mathematics ...

deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ML services (SageMaker, Vertex AI, or Azure ML) Strong software engineering practices: version control, testing, CI/CD MSc or PhD in Computer Science, Machine Learning ...

Environment Languages/Tools: Python (NumPy, Pandas, Scikit learn), deep learning frameworks (PyTorch/TensorFlow), SQL. MLOps: MLflow, cloud ML platforms (Azure ML, AWS SageMaker, or Databricks). Focus areas: Predictive modelling, recommender systems/personalisation, and increasingly, applied LLM/GenAI use cases, reflecting where the market ...

self-serve. You will work across a hybrid/remote setup with flexible working and travel to client sites as needed. Strong AWS, SageMaker, and Python expertise are essential. #J-18808-Ljbffr ...

dashboards, alerting, and MS Teams integrations—and reduce incidents via telemetry-driven automation and blameless postmortems. Champion AI‐enabled operations using AWS Bedrock/SageMaker and Model Context Protocol (MCP) for log analysis, anomaly detection, incident triage, and workflow orchestration; establish adoption guardrails. Define and enforce cloud guardrails … operations—incident triage, runbooks, and change management—with clear guardrails, auditability, and human-in-the-loop controls. Supporting AI/ML workloads at scale: SageMaker endpoints, GPU node groups, autoscaling, and Kubernetes-based model serving. Policy-as-code (OPA) and compliance implementation across CIS, NIST, ISO 27001, with automated ...

development programme that will allow you the freedom to take on training and certifications on the training platform of your choice. As an Amazon Web Services (AWS) cloud architect, you'll assist in implementing and supporting large-scale cloud implementations on Amazon AWS. Other duties include architecting … depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype environments to enterprise‐ready architectures, balancing speed, robustness ...

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