1 to 25 of 89 Amazon SageMaker Jobs in the UK

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 ...

that fuel analytics, AI/ML, and data-driven operations.* Design and build high-performance data integration solutions: Use AWS Glue, AWS Step Functions, Amazon EventBridge, and AWS Database Migration Service (DMS) to orchestrate ingestion, transformation, and movement of data across on-premises and cloud sources into Amazon … Design and oversee the delivery of secure lakehouse and warehouse architectures: Implement logical and physical data models, data quality controls, and governance practices using Amazon S3 (data lake), AWS Lake Formation, Amazon Redshift, and Amazon Athena to ensure trusted data.* Ability to design AI/ML-enabled ...

Technical Stack & Requirements: AI/ML Stack: Amazon SageMaker, AWS Bedrock. Design Focus: Vector databases, knowledge graphs, and semantic layers. Databricks: Experience with Databricks and Databricks Genie is highly desirable. Core Mandate: Define the standards for "AI-ready" data curation and direct the integration of AI methodologies into … architectures. Excellent communication and stakeholder management skills. Preferred Qualifications Experience with Agentic AI frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel). Experience with AWS Bedrock, Amazon SageMaker, Azure OpenAI, or Vertex AI. Experience implementing Responsible AI frameworks. Financial services, fintech, or investment management domain experience. Experience building recommendation engines ...

particularly Data Loss Prevention (DLP), Information Protection, and Insider Risk Management, and how these underpin safe enterprise AI adoption Familiarity with Azure AI Foundry, Amazon Bedrock, or Amazon SageMaker; Google Vertex AI experience a bonus Understanding of data readiness principles for AI, including permissions hygiene, oversharing remediation … Software as a Service (SaaS), and serverless architectures Understanding of enterprise AI deployments (e.g., Microsoft 365 Copilot rollouts, Copilot Studio agents, Azure AI Foundry, Amazon Bedrock, Amazon Q Business, Google Vertex AI, or Gemini for Google Workspace) Strong project management and stakeholder communication skills Experience architecting solutions ...

integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacks Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed model hosting Experience with online large language model quality monitoring, including hallucination detection ...

integrating model serving platforms such as KServe, Ray Serve, or NVIDIA Triton Inference Server alongside other large language model serving stacks Familiarity with Amazon SageMaker JumpStart, SageMaker Endpoints, and Amazon Bedrock for managed model hosting Experience with online large language model quality monitoring, including hallucination detection ...

models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing and statistical evaluation Proven experience moving models from experimentation into production ...

record building and maintaining CI/CD pipelines (GitHub Actions, CircleCI, Jenkins, GitLab CI) Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments) Proficiency in scripting and automation (Python, Bash, Go) Strong experience with monitoring and observability tools (CloudWatch, Prometheus, Grafana, Datadog, Sentry ...

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 ...

serving: NVIDIA Triton, vLLM, TensorRT-LLM, or equivalent high-throughput serving platforms. MLOps/LLMOps: Kubeflow, MLflow, and at least one hyperscaler ML platform (SageMaker, Azure ML, or Vertex AI). Generative AI: LLM fine-tuning (LoRA/QLoRA), RAG architecture design, vector databases (Pinecone, Milvus, Weaviate), and agentic ...

training,evaluationand production deployment, includingMLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn,PyTorch,XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Platform & Cloud Engineering: Architecture and delivery of scalable cloud data and AI platforms on AWS,Azureor GCP; experienced with ...

Software Dev Engineer, Amazon Security Automation Job ID: 10498444 | Amazon UK Services Ltd. At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products … NextGen Security Automation team is looking for a skilled and driven Software Development Engineer (SDE II) to build autonomous security solutions that protect Amazon’s customers. As an SDE II, you will leverage AI/ML technologies to automate detection, analysis, and response across proactive, offensive, and defensive security ...

architecture strategy. Keep us ahead of AWS roadmaps in priority services, and set the technical bar as the alliance scales. Technical Depth Generative AI: Amazon Bedrock, SageMaker, agentic and generative AI application patterns Data & Analytics: Amazon Marketing Cloud (AMC), AWS Clean Rooms, data lakes, analytics pipelines Customer … Experience: Amazon Personalize, Amazon Connect, serverless architectures Modern Applications: Lambda, Step Functions, API Gateway, container orchestration Integration: Event-driven architectures, microservices, API design How Success Looks Technical win rate on the strategic pursuits you lead Competitive deals turned in our favor by your technical credibility Reference architectures adopted ...

Agile environment Databricks Strong programming skills in Python, SQL and/or Spark AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology) Hands-on experience with ML model deployment, monitoring and life cycle management Experience building and maintaining data ...

deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ML services (SageMaker, Vertex AI, or Azure ML) Strong software engineering practices: version control, testing, CI/CD MSc or PhD in Computer Science, Machine Learning ...

Awareness of ethical, privacy, security and policy considerations in applied AI Desirable Experience Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow) Experience working in government, defence or other highly regulated environments Proven application ...

with Cloud services, Infrastructure as Code (IaC) and containerized application development Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) Experience working on AIML systems and/ ...

. Hands‐on experience with GCP Vertex AI (model endpoints, pipelines, embeddings, vector search) or equivalent cloud‐native AI/ML platforms (e.g. AWS SageMaker, AzureML) and agent orchestration frameworks (e.g. LangChain, LangGraph, ADK). Solid understanding of MLOps – CI/CD, IaC (Terraform), experiment tracking, model registry ...

managing production APIs. Software Engineering Best‐Practices: Knowledge of industry standards and practices. Preferred Qualifications: AWS AI Services: Hands‐on experience with AWS SageMaker and/or AWS Bedrock. Data Processing: Experience with high‐volume, unstructured data processing. ML Applications: Familiarity with NLP, Computer Vision, and traditional ML applications. ...

Retrieval-Augmented Generation (RAG) AI Agents and Agentic AI Multi-agent systems Voice AI Speech-to-text/text-to-speech ElevenLabs AWS Bedrock Amazon SageMaker Google Cloud Platform (GCP) Vertex AI Python FastAPI/APIs LangChain/LangGraph Vector databases Embeddings and semantic search Hugging Face/ ...

with Cloud services, Infrastructure as Code (IaC) and containerized application development Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps) Experience working on AIML systems and/ ...

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 ...

Expertise with modern data platforms (e.g., BigQuery/Databricks) and data processing workflows (ETL, pipelines). Excellent experience with cloud hosted AI platforms (Bedrock, Sagemaker, VertexAI) Strong problem-solving abilities, with the capacity to learn quickly and adapt in a fast-paced environment. Excellent communication and a drive ...