1 to 25 of 89 Amazon SageMaker Jobs in the UK

Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within: Microsoft Azure Google Cloud Platform (GCP) Additional experience with: Docker Kubernetes Git CI/CD Pipelines ...

Data Pipeline Engineering Vector Databases such as Pinecone, Weaviate or ChromaDB Cloud & DevOps Experience with at least one major cloud platform: AWS (preferred) Bedrock SageMaker Lambda ECS/EKS S3 Or experience within: Microsoft Azure Google Cloud Platform (GCP) Additional experience with: Docker Kubernetes Git CI/CD Pipelines ...

underfitting, data leakage, and drift. You will use your expertise in engineering and DevOps/MLOps to manage our machine learning platforms using AWS SageMaker and other AWS services. You will: Design, build, and improve scalable public cloud‐based machine learning platforms. Develop robust data pipelines and workflows, contributing … while mastery of all these areas isn’t required, familiarity with as many as possible will be advantageous. Cloud and Infrastructure Infrastructure as Code: Amazon CDK ML Platform: Amazon SageMaker (SagemakerStudio IDE, SagemakerTraining/Processing/Pipeline/Endpoints, Feature Store, Model Registry, Model Monitor) Data Processing ...

Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication and collaboration skills, with the ability to translate complex technical concepts for diverse, cross-functional stakeholders. ...

practice in Python. Familiarity with popular machine learning libraries and frameworks such as scikit‐learn, Hugging Face, PyTorch and TensorFlow. Experience with MLFlow, AWS SageMaker and Bedrock is preferred. Familiar with MLOps concept. Comfortable with data cleansing using SQL and PySpark. Good written and oral communication skills, including ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

frameworks (LangChain, LlamaIndex, AutoGen). Data Engineering : ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures. Cloud Platforms : AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery). MLOps : Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment ...

with strong technical leadership capability Key Skills Python (or similar programming languages) TensorFlow, PyTorch, or similar ML frameworks Cloud AI services (Azure AI, AWS SageMaker, GCP AI Platform) Data technologies (SQL/NoSQL, Spark, Databricks) API and microservices architecture DevOps/MLOps tooling Desirable Experience Experience with Generative ...

compliance (Zero Trust architectures, identity‐aware AI access, secrets management) AI/ML platforms, responsible AI practices, and model lifecycle management (MLflow, Vertex AI, SageMaker, Azure ML, Arize, Azure AI Studio) Design and operationalize enterprise‐scale GenAI and agent‐based solutions. Experience with modern AI architectures including Retrieval‐Augmented ...

engineering agentic AI systems • Knowledge of the healthcare/pharma domain and experience applying AI to healthcare data • Experience with AWS, especially ECS, Bedrock, SageMaker, serverless compute, and storage • Ability to prototype proof-of-concept web applications with familiarity across the full stack • Expert usage of AI coding tools ...

deep learning ecosystems, specifically PyTorch or TensorFlow, alongside core toolkits like OpenCV. Strong experience deploying vision models at scale using AWS tools (e.g., Amazon EC2 GPU instances, Amazon SageMaker) alongside model optimisation frameworks like TensorRT or ONNX. Extensive experience working within fast‐paced Agile delivery teams using ...

experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio) Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop ...

engineering agentic AI systems Knowledge of the healthcare/pharma domain and experience applying AI to healthcare data Experience with AWS, especially ECS, Bedrock, SageMaker, serverless compute and storage Ability to prototype PoC webapps with familiarity across the full stack Expert usage of AI coding tools and workflows ...