4 of 4 Amazon SageMaker Jobs in the South East

facing or product-centric ML systems. A product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes: AWS or GCP environments (SageMaker, Bedrock, Lambda, S3, Redshift). MLOps practices (monitoring, deployment, optimisation). Working with streaming data, transformer models or recommendation systems. What They Offer ...

Proficiency in Python and common ML frameworks such as PyTorch, TensorFlow, or scikit-learn * Exposure to ML/MLOps tooling such as SageMaker, MLflow, or TFServing * Experience with Spark, Databricks, CI/CD tools, and streaming or orchestration systems like Kafka or Airflow How to Apply ...

designing large-scale digital transformation solutions - including AI, data platforms, and cloud architectures. AI & Data Expertise in AI/ML platforms (Azure AI, AWS SageMaker, Google Vertex AI), data governance, analytics, and responsible AI practices. Cloud & Integration Strong understanding of hybrid and multi-cloud architectures, APIs, microservices, and event ...

model performance, data drift, and system health to ensure reliability and availability. Support ML platforms and infrastructure on-premise or in the cloud (AWS, SageMaker), ensuring scalability and security. Collaborate with data scientists to productionise models and embed ML Ops best practices across the organisation. Ensure governance, compliance, documentation … model maintenance. Hands-on experience with Python (and ML frameworks), containerisation (Docker/Kubernetes), CI/CD pipelines, and cloud ML services (AWS SageMaker preferred). Experience with infrastructure-as-code, production-grade Linux environments, and API services (Flask/Gunicorn). Proficiency in building automated, reliable ML pipelines ...