1 to 25 of 45 Amazon SageMaker Jobs in the South West

the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure More ❯

the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure More ❯

the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure More ❯

reusable code Strong communication and collaboration skills Desirable: Experience with LLM tools (e.g. LangChain) Background in ML Ops, serverless/containerised infrastructures (e.g. Kubernetes, SageMaker) Send across your latest CV to apply More ❯

a product-focused SaaS environment. Strong command of Python and relevant libraries for machine learning, data engineering, and automation. Experience working with AWS (e.g., SageMaker, Bedrock) and infrastructure-as-code tools like Terraform. Solid understanding of large-scale data pipelines, distributed systems, and microservice architectures. Comfortable working with LLMs More ❯

a product-focused SaaS environment. Strong command of Python and relevant libraries for machine learning, data engineering, and automation. Experience working with AWS (e.g., SageMaker, Bedrock) and infrastructure-as-code tools like Terraform. Solid understanding of large-scale data pipelines, distributed systems, and microservice architectures. Comfortable working with LLMs More ❯

a product-focused SaaS environment. Strong command of Python and relevant libraries for machine learning, data engineering, and automation. Experience working with AWS (e.g., SageMaker, Bedrock) and infrastructure-as-code tools like Terraform. Solid understanding of large-scale data pipelines, distributed systems, and microservice architectures. Comfortable working with LLMs More ❯

a product-focused SaaS environment. Strong command of Python and relevant libraries for machine learning, data engineering, and automation. Experience working with AWS (e.g., SageMaker, Bedrock) and infrastructure-as-code tools like Terraform. Solid understanding of large-scale data pipelines, distributed systems, and microservice architectures. Comfortable working with LLMs More ❯

business in their Data Science, AI, and ML initiatives. Our Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. We are currently engaged on multiple data focused projects which are in various stages More ❯

business in their Data Science, AI, and ML initiatives. Our Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. We are currently engaged on multiple data focused projects which are in various stages More ❯

automation tools and libraries. Excellent problem-solving and analytical skills Strong communication and teamwork abilities Preferred Skills : Good to have experience with AWS Bedrock, SageMaker and Databricks Familiarity with CI/CD pipelines and tools like Jenkins, Docker, Kubernetes Experience with cloud tools like Kubernetes, EKS, AWS Glue, ECS More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, or similar. Experience with CI/CD for AI (GenAIOps), model monitoring, and cloud platforms: Google Vertex AI, AWS SageMaker, or Azure AI. Knowledge of AI security, model explainability, and Responsible AI principles. Experience building or integrating voice-enabled chatbots and multi-modal systems. More ❯

honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks As an inclusive employer, we want to ensure that all candidates feel comfortable and can perform at their More ❯

honesty. Nice to have: Knowledge of R or other programming languages Knowledge of current UK AI/ML compliance and regulation. Experience with AWS Sagemaker Experience with Snowflake Experience with Databricks As an inclusive employer, we want to ensure that all candidates feel comfortable and can perform at their More ❯

encryption key management processes and systems. Ensure security across the Data & Analytics technology stack consists primarily of: Oracle tools, Snowflake, Postgres, various AWS Services (SageMaker, Lambda, Step Functions, DMS, S3 etc.) in the AWS Cloud. Data Security Engineer - Your Background The ideal Data Security Engineer will have: Experience in More ❯

British nationality are mandatory due to project sensitivity. Desirable: Experience in defence or government programmes . Familiarity with cloud-based ML toolsets (e.g., AWS SageMaker Ground Truth, Azure Custom Vision). Knowledge of computer vision models and their data requirements. Experience managing annotation teams or quality control processes. Additional More ❯

British nationality are mandatory due to project sensitivity. Desirable: Experience in defence or government programmes . Familiarity with cloud-based ML toolsets (e.g., AWS SageMaker Ground Truth, Azure Custom Vision). Knowledge of computer vision models and their data requirements. Experience managing annotation teams or quality control processes. Additional More ❯

British nationality are mandatory due to project sensitivity. Desirable: Experience in defence or government programmes . Familiarity with cloud-based ML toolsets (e.g., AWS SageMaker Ground Truth, Azure Custom Vision). Knowledge of computer vision models and their data requirements. Experience managing annotation teams or quality control processes. Additional More ❯

to build and optimize ML models that improve search engine accuracy and efficiency. Experience in similar projects is highly advantageous. Proficiency in Python, AWS, SageMaker, A/B Testing Experience with AI/ML search engine projects Effective communication skills and ability to work under pressure Position inside IR35 More ❯