1 to 25 of 88 Permanent Amazon SageMaker Jobs in London

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 … priority for Amazon. Please consult our Privacy Notice () to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive ...

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 ...

/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 ...

Docker/Kubernetes). Strong background in data modelling, warehousing, and supporting analytical and ML workloads. Exposure to MLOps tools including MLFlow, kedro and Amazon Sagemaker. Development and maintenance of real time products like APIs using FastAPI/Flask. Operates autonomously with strong ownership and accountability. Strategic thinker ...

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 ...

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). Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure or GCP; experienced with containerisation, IaC, event ...

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 ...

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 ...

. 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 ...

lifecycle. What you’ll be doing Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton Support AI scientist creating reproducible, containerized model training environments (on-demand and scheduled), and manage compute at scale (e.g., spot/GPU autoscaling) Define ...

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 ...

FastAPI, testing, and typing; Experience with cloud-native development, preferably GCP; Hands-on experience with GCP Vertex AI or equivalent platforms such as AWS SageMaker or Azure ML; Experience with agent orchestration frameworks such as LangChain, LangGraph, or ADK; Solid understanding of MLOps, including CI/CD, Terraform, experiment ...

including Docker and/or Podman . Practical cloud experience across one or more of AWS, Azure or GCP , ideally using services such as SageMaker, Azure ML or Vertex AI. Experience with CI/CD and MLOps tooling such as GitLab CI, GitHub Actions, Jenkins, Kubeflow or MLflow . ...

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 ...

Migration tooling: AWS MGN, AWS DMS, AWS DataSync, AWS SCT, and AWS MAP framework Data and AI platform: AWS Glue, Kinesis, Lake Formation, Bedrock, SageMaker — for integrated data platform and agentic AI roadmap phases Apply Azure/GCP knowledge to extend solution coverage on multi-cloud or Azure-primary ...

everything that gets those models in front of a customer and keeps them running: the training and deployment infrastructure on AWS and SageMaker, reproducible and configuration-driven training runs, environments defined in code, release pipelines that make a deployment routine rather than an event, and the monitoring that tells … machine learning engineers/scientists and turn them into production services that meet our latency, cost and reliability targets. Build and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them. Make training runs reproducible and configuration-driven, so any result can be rebuilt from code. ...

machine learning engineers/scientists and turn them into production services that meet our latency, cost and reliability targets. Build and maintain SageMaker training, processing and inference workloads, and the pipelines that orchestrate them. Make training runs reproducible and configuration‐driven, so any result can be rebuilt from code. … PyTorch experience (TensorFlow also welcome) and the surrounding ecosystem: Hugging Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‐driven ...

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/ ...

practices to confirm they catch degradation before it costs the business.You'll assess CI/CD and deployment controls — Docker, Jenkins, and the AWS SageMaker, S3, Athena, and Lambda environments models run in.You'll evaluate model governance documentation, explainability approaches, and compliance with regulatory expectations on model risk, fairness ...

resolve blockers, and deliver results with a strong sense of urgency It’s a bonus if you have Experience with MLFlow/model versioning, SageMaker Pipelines, or Databricks Familiarity with real-time, high-volume data products and low-latency data stores (e.g. DynamoDB) Automated testing and validation frameworks ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands‐on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Equal Opportunity Employer We recognize that our people are our strength ...

frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost, latency, performance, security, and scaling Experience integrating human ...

Experience Proven experience designing and deploying production-grade AI/ML or LLM systems . Expertise with AWS or Azure AI services (e.g., Bedrock, SageMaker, OpenAI, Cognitive Services). Strong Python programming skills with hands‐on experience using frameworks like Autogen and LangGraph . Solid grounding in MLOps , containerisation ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands-on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Join us to help shape the future of Market Operations through ...

prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites. Hands-on experience with agentic frameworks (LangChain, LangGraph). Experience with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration. Demonstrated experience in financial services, particularly investment banking operations. Join us to help shape the future of Market Operations through ...