1 to 25 of 133 Permanent Amazon SageMaker Jobs in London

live services, and play a key role in resolving complex production issues.Stay up to date with the latest technologies and AWS services, including Amazon Bedrock and Amazon Q Business, to enhance client capabilities and foster innovation.Actively contribute to the engineering community.Contribute to technical pre-sales activity, including … 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 ...

resilient AWS environments.AWS technologies and services across compute, storage, networking, databases, analytics, integration, security and management.AI and machine learning services on AWS, including Amazon Bedrock, Amazon SageMaker AI, Amazon Q, Amazon Comprehend, Amazon Transcribe, Amazon Rekognition and related managed AI services.Generative AI solution … ingestion, governance, feature management, model lifecycle management, MLOps, observability and secure deployment of AI workloads.Container technologies such as Docker and associated orchestration platforms including Amazon EKS, Kubernetes, Amazon ECS and OpenShift.Infrastructure as code development using Terraform, AWS CloudFormation, AWS CDK and associated configuration management approaches.Cloud automation tooling ...

environments.· AWS technologies and services across compute, storage, networking, databases, analytics, integration, security and management.· AI and machine learning services on AWS, including Amazon Bedrock, Amazon SageMaker AI, Amazon Q, Amazon Comprehend, Amazon Transcribe, Amazon Rekognition and related managed AI services.· Generative … governance, feature management, model lifecycle management, MLOps, observability and secure deployment of AI workloads.· Container technologies such as Docker and associated orchestration platforms including Amazon EKS, Kubernetes, Amazon ECS and OpenShift.· Infrastructure as code development using Terraform, AWS CloudFormation, AWS CDK and associated configuration management approaches.· Cloud automation ...

models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon Q, or Amazon Rekognition is highly valued. Experience architecting end-to-end ML pipelines including data … Objects, etc.) and their architecture and infrastructure needs Experience in infrastructure architecture, database architecture and networking Experience working with end user or developer communities Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based ...

models, retrieval-augmented generation (RAG), fine-tuning, prompt engineering, or agentic AI architectures. Hands-on experience with AWS AI/ML services such as Amazon Bedrock, Amazon SageMaker, Amazon Q, or Amazon Rekognition is highly valued. Experience architecting end-to-end ML pipelines including data ...

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 ...

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 ...

/or Java/Scala, with clean coding, testing and code review practices. Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, Databricks, or equivalent. Proven experience with Kubernetes, Docker, Helm and infrastructure as code (Terraform/CloudFormation). Cloud experience with AWS, Azure ...

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

containerization technologies like docker, Kubernetes, AWS EKS etc.Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g. AWS Bedrock,AWS S3, AWS Sagemaker, Azure AI search, Azure OpenAI, Azure blob storage etc.Master's degree or above in Machine learning/data science, computer science, applied mathematics ...

frameworks.Inference & 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 frameworks ...

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 frameworks ...

architecture strategy. Keep us ahead of AWS roadmaps in priority services, and set the technical bar as the alliance scales.Technical DepthGenerative AI: Amazon Bedrock, SageMaker, agentic and generative AI application patternsData & Analytics: Amazon Marketing Cloud (AMC), AWS Clean Rooms, data lakes, analytics pipelinesCustomer Experience: Amazon Personalize … Amazon Connect, serverless architecturesModern Applications: Lambda, Step Functions, API Gateway, container orchestrationIntegration: Event-driven architectures, microservices, API designHow Success LooksTechnical win rate on the strategic pursuits you leadCompetitive deals turned in our favor by your technical credibilityReference architectures adopted as reusable standards across the alliancePOC-to-production conversion ...

RFPs/tenders; experience running hands-on product demos independently. Knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on-premise, and hybrid deployment models. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, safetensors ...

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

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 ...

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 ...

Experience in a specific domain relevant to the business (e.g., banking, financial services, insurance). Exposure to MLOps/LLMOps tooling (MLflow, Vertex AI, SageMaker, Azure AI Studio). Experience presenting architecture and AI strategy to senior/executive stakeholders. HCLTech is an equal opportunity employer, committed to providing ...

. 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 ...

frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain,Langsmith/Langfuse, Gen AI/Agentic AI , Cloud platforms (Azure AI Foundry, AWS Bedrock/Sagemaker, GCP Vertex AI) , MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes).Preferred•Delivered AI projects within Agile frameworks•Experience on Gen AI Feedback Analysis, topic ...

production deployment, including MLOps, 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). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

production deployment, including MLOps, 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). Software Engineering: Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js ...

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/ ...

Models (SLMs). Infrastructure & Operations Containers: Advanced knowledge of Docker, Podman, and container orchestration. Cloud Providers: Practical experience managing AI workloads on AWS (EC2, SageMaker), Azure (Azure ML), and GCP (Vertex AI). CI/CD Tools: Experience with GitLab CI, GitHub Actions, Jenkins, or specialized MLOps platforms (e.g. ...