1 to 25 of 39 Amazon SageMaker Jobs in the UK excluding London

Support and mentor less-experienced engineers through code reviews, pairing, technical guidance, and knowledge sharing. Stay current with AWS services and engineering approaches, including Amazon Bedrock and Amazon Q Business, and propose relevant innovations for client delivery. Contribute to the engineering community through learning sessions, reusable assets, methods … focus on AWS. Experience understanding client requirements and solving problems within multidisciplinary delivery teams. Hands-on delivery experience across AWS services such as Amazon EC2, Amazon EKS, Amazon RDS, Amazon Redshift, Amazon S3, Amazon VPC, AWS IAM, AWS Lambda, AWS App Runner ...

maintaining cloud-based platforms and infrastructure, with a focus on AWS. Hands on experience with AWS, including practical delivery across core services such as Amazon EC2, Amazon EKS, Amazon RDS, Amazon Redshift, Amazon S3, Amazon VPC, AWS Identity and Access Management (IAM), AWS Lambda … identity management in cloud environments, including AWS-specific best practices. Familiarity with monitoring, logging, and alerting tools (e.g., Prometheus, Grafana, the ELK stack, Amazon CloudWatch, and AWS X-Ray). Experience with version control systems (e.g., Git) and scripting languages (e.g., Python, Bash, Go). Ability to troubleshoot ...

infrastructure and platform solutions. Foundational understanding of AWS services, cloud infrastructure and modern engineering practices. Experience with one or more AWS services such as Amazon EC2, Amazon S3, Amazon RDS, Amazon VPC, AWS IAM or AWS Lambda. Understanding of Infrastructure as Code principles and tools such … hybrid and multi-cloud architectures, including the integration of on-premises environments with AWS. Awareness of AI and machine learning services on AWS, including Amazon SageMaker, Amazon Bedrock and Amazon Q Business. Awareness of AWS billing, cost management and optimisation services, including AWS Cost Explorer ...

Desirable (Nice to Have) Experience with streaming and big‐data tooling – Apache Kafka, Spark, or Flink Experience with MLOps platforms – MLflow, Kubeflow, Vertex AI, SageMaker, or Weights & Biases Experience evaluating and optimising RAG systems at scale (retrieval quality, chunking, re‐ranking) Experience designing multi‐agent systems and agent orchestration ...

Evaluation Frameworks. Experience with LangChain, LangGraph, Semantic Kernel, and AutoGen. Hands-on experience with Azure AI Foundry/Azure OpenAI, AWS Bedrock and SageMaker, Google Vertex AI, and hybrid and multi-cloud architectures. Strong programming experience with Python, Java, Scala, TypeScript, and SQL. Experience with Kubernetes, Docker, Terraform, Bicep ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

deploy machine learning models and statistical analyses in production environments Architect and manage AWS cloud infrastructure for data workloads (S3, Lambda, Glue, Athena, SageMaker, Step Functions) Collaborate with domain experts to translate rail inspection requirements into technical solutions Write clean, tested, well-documented code following engineering best practices Participate ...

deploy machine learning models and statistical analyses in production environments Architect and manage AWS cloud infrastructure for data workloads (S3, Lambda, Glue, Athena, SageMaker, Step Functions) Collaborate with domain experts to translate rail inspection requirements into technical solutions Write clean, tested, well-documented code following engineering best practices Participate ...

building agentic AI systems (multi-step workflows, tool routing, planning, memory patterns, supervision/fallback strategies). Experience with AWS Bedrock and/or SageMaker (or equivalent managed ML/GenAI platforms) and deployment patterns for scalable inference. Experience with evaluation frameworks and approaches (golden datasets, LLM-as-judge ...

scaling AI solutions using at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker)* Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK* Hands-on experience ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

experience of building data pipelines using Spark, Python or SQL - Experience working with AWS and its data and AI/ML services such as SageMaker - Experience of big data and lakehouse platforms on AWS (EMR, Databricks or Snowflake) - Experience building data platforms such as Data Lakes, Lakehouses or Data ...

applications (RAG, tool use, multi-step workflows) for client projects and internal products. Take them from prototype to production on AWS or Azure (e.g. SageMaker, Azure ML, Databricks, OpenAI integrations), then monitor and improve them once they are live. Explore and understand client data before building anything. Design evaluation ...

calibration)• Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust)MLOps & LLMOps• Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector)• Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks• Exposure to fine-tuning ...

calibration) • Guardrail and AI-observability tooling (e.g. NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust) MLOps & LLMOps • Hands-on with MLOps platforms (Azure ML, Databricks, SageMaker) and vector/retrieval databases (Pinecone, Milvus, pgvector) • Experience with GPU-accelerated infrastructure and NVIDIA AI Enterprise or equivalent stacks • Exposure to fine-tuning ...

with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

with MLOps in practice rather than in principle: model versioning and registries, experiment tracking, automated retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise ...

production Strong Python development skills Hands-on experience with LangGraph, LangChain, LlamaIndex, CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with ...

Genomics, digital pathology, structural biology or other high‐volume scientific data modalities and formats. AWS CDK, Batch, ECS, EKS, S3, RDS or Postgres, Athena, SageMaker, Bedrock, or equivalent services. Scientific workflow and data orchestration frameworks such as Nextflow, Dagster, Airflow or similar. Platform security, privacy or governance controls ...

technical excellence. Qualifications Proficiency in Python and C#. SQL or R is a plus. Experience with Cloud AI services such as Azure ML, AWS SageMaker, GCP Vertex AI. Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such ...

Experience in all architecture domains:- application, data, cloud ( AWS) and technology with expertise with AI, Gen Ai and ML frameworks (e.g., TensorFlow, PyTorch, AWS Sagemaker, AWS Bedrock, OpenAI). Strong experience of AI services and AI lifecycle and model training* Proficiency in backend and frontend technologies such as .NET ...

libraries, frameworks and services : such as ML libraries e.g. TensorFlow or PyTorch; model servers such as AWS Bedrock; MLOps such as ML Flow or Sagemaker; agent/AI orchestration such as LangGraph or MCP libraries Strong programming skills, especially in Python (other languages like C++, Scala, Rust ...

commercially credible solutions developed. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise, Dell AI Factories) Understanding of data engineering practices (ETL, data lakes ...