1 to 25 of 117 Amazon SageMaker Jobs in the UK

ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD, Docker, AWS (S3, Lambda, SageMaker), Kubernetes, Terraform/CDK ML Ops & Automation: MLFlow, feature stores, model monitoring, A/B testing Data Security & Compliance: Secure SDLC, ISO/NIST ...

least one major cloud provider. AWS, GCP or Azure Familiar with Docker and CI/CD pipelines Experience with managed ML platforms such as SageMaker, Vertex AI or Azure ML Data engineering and MLOps Experience with data warehouses such as Snowflake, BigQuery or Redshift Workflow orchestration using tools like ...

Shapely, and GDAL Advanced knowledge of PostgreSQL/PostGIS for spatial data management Experience with AWS and Azure platforms, including AI services (e.g., AWS SageMaker, Azure ML) Proven experience developing or deploying AI models across domains such as natural language processing, computer vision, or predictive analytics Familiarity with machine ...

vector databases (Pinecone, Weaviate, OpenSearch), or multi-agent orchestration. Experience building conversational agents or AI-driven automation systems. Knowledge of MLOps tooling such as SageMaker, MLflow, or Databricks. Familiarity with RLHF, alignment techniques, or model interpret ability. Interest in consumer behaviour, research methodologies, or product decision-making. Startup experience ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...

with building ML services using Python web frameworks such as FastAPI or stream processing libraries like Faust. Experience using tools like Jupyter Notebooks, AWS SageMaker, and AWS Bedrock. Hands-on expertise with Kafka and vector databases. Experience managing ML lifecycle workflows with MLflow. Deep understanding of LLMs and generative ...