18 of 18 Permanent Amazon SageMaker Jobs in the UK excluding London

including model hosting, request routing, continuous batching, and KV‐cache optimization Deploy, host, and lifecycle‐manage open‐source and proprietary LLMs on Amazon EKS and Amazon SageMaker, as well as on‐prem and local GPU clusters, using reproducible infrastructure as code and continuous delivery pipelines Implement observability … experience operating LLM inference servers such as vLLM and llm‐d (or directly equivalent serving stacks) Hands‐on experience hosting and serving LLMs on Amazon EKS and/or Amazon SageMaker, and on local GPU infrastructure Knowledge of LLM reliability and risk considerations, including latency/throughput ...

backend services and APIs that enable reliable operation of AI infrastructure in production Deploy, host, and lifecycle-manage open-source and proprietary LLMs on Amazon EKS and Amazon SageMaker, as well as on-prem and local GPU clusters, using reproducible infrastructure as code and continuous delivery pipelines … experience operating LLM inference servers such as vLLM and llm-d (or directly equivalent serving stacks) Hands-on experience hosting and serving LLMs on Amazon EKS and/or Amazon SageMaker, and on local GPU infrastructure Knowledge of LLM reliability and risk considerations, including latency/throughput ...

deploying Machine Learning models using Python Experience with frameworks such as PyTorch, TensorFlow, Scikit-learn or XGBoost Knowledge of AWS cloud services including SageMaker, Lambda and S3 Experience with MLOps tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge ...

/CD pipelines, model versioning, and monitoring. Comprehensive experience with cloud platforms (AWS, Azure, or GCP) and cloud native AI tools, such as SageMaker, Vertex AI, or Azure ML Studio. Ability to design and deploy cloud-based AI solutions. Proficiency in using containerization technologies (e.g., Docker) and orchestration tools ...

including CI/CD pipelines, model versioning, and monitoring. Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native AI tools such as SageMaker, Vertex AI, or Azure ML Studio. Working knowledge of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) to build and manage scalable ...

performance and reliability. Build and integrate AI-driven features (LLMs, intelligent APIs, automation workflows). Implement RAG patterns, AI pipelines, and model integrations (Bedrock, SageMaker). Optimize and monitor models for accuracy, drift, bias, and observability. Leverage Claude/equivalent frontier models to engineer solutions Notes on the role ...

tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation, A/B testing and online evaluation ...

tools, and raising potential risks to senior colleagues. Basic understanding of cloud platforms (AWS, Azure, or GCP); exposure to cloud-native AI tools (e.g., SageMaker, Vertex AI, Azure ML Studio) is a plus. Awareness of containerisation technologies (e.g., Docker); exposure to orchestration tools (e.g., Kubernetes) is beneficial ...

integrating generative AI tooling. Understanding of secure software development, cloud cost optimization, and platform observability. Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. ...

developing a growing team of Data Scientists Establishing best practice across model development, governance and MLOps Tech Stack Python | SQL | TensorFlow | PyTorch | AWS | Azure | SageMaker | NLP | LLMs | MLOps What we're looking for: Strong commercial Data Science and Machine Learning experience Experience leading teams or acting as a technical ...

documentation and collaborate across engineering teams. Ecosystem Knowledge : Hands-on experience supporting software delivery and MLOps tooling (e.g., Kubernetes, Kubeflow, MLflow, Triton, Docker, or SageMaker/Azure ML) Equal Opportunity Statement We are committed to fostering and promoting an inclusive professional environment for all of our employees ...

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 ...

ability to present complex information through clear and compelling data visualisations, ideally using Tableau Experience of cloud-based data science technologies, ideally including AWS SageMaker, AWS Bedrock and Snowflake , would be highly desirable A passion for continuous learning and staying up to date with emerging data science tools, technologies ...

ability to present complex information through clear and compelling data visualisations, ideally using Tableau Experience of cloud-based data science technologies, ideally including AWS SageMaker, AWS Bedrock and Snowflake , would be highly desirable A passion for continuous learning and staying up to date with emerging data science tools, technologies ...

strong expertise in SQL and Python being desirable. We're utilising the Data Science tools in the AWS Stack, so a good understanding of Sagemaker, Bedrock, and AWS Cloud Components would be highly desirable. Snowflake is our Central Data Platform, of which some experience would be desirable. Demonstrable experience ...

strong expertise in SQL and Python being desirable. We're utilising the Data Science tools in the AWS Stack, so a good understanding of Sagemaker, Bedrock, and AWS Cloud Components would be highly desirable. Snowflake is our Central Data Platform, of which some experience would be desirable. Demonstrable experience ...

demonstrate excellent technical capabilities, including proficiency in Python, SQL and Git. Practical experience deploying machine learning models within cloud-based environments, particularly using AWS SageMaker, will be highly advantageous. Candidates should possess a solid understanding of statistical modelling techniques and demonstrate a genuine enthusiasm for machine learning, predictive analytics ...

aware performance tuning. You will own reliability, performance, and cost efficiency of the LLM platform end-to-end, manage diverse hosting environments including EKS, SageMaker, and on‐prem GPU clusters, and lead incident response with strong #J-18808-Ljbffr ...