1 to 25 of 32 Permanent Amazon SageMaker Jobs in London

Azure AI Foundry, Azure AI Search (vector/RAG), Azure Machine Learning, Azure AI Agent Service, Semantic Kernel, Prompt Flow and Content Safety. AWS: Amazon Bedrock (including Knowledge Bases and Agents), Amazon SageMaker, Amazon Q, Amazon OpenSearch (vector), and Guardrails for Amazon Bedrock. Expertise ...

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 ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/B testing methodology, and statistical evaluation Proven track record transitioning models ...

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 ...

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 ...

least one major cloud provider. AWS, GCP or AzureFamiliar with Docker and CI/CD pipelinesExperience with managed ML platforms such as SageMaker, Vertex AI or Azure MLData engineering and MLOpsExperience with data warehouses such as Snowflake, BigQuery or RedshiftWorkflow orchestration using tools like Airflow or DagsterExperience with MLOps ...

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 ...

strongly preferred) Production ML engineering excellence – Strong understanding of MLOps, containerization (Docker, Kubernetes/AWS EKS), cloud platforms (AWS/Azure including Bedrock, SageMaker, Azure AI Search), workflow orchestration (Airflow), and API development for ML systems Software development fundamentals – Deep understanding of automated testing, source version control, code optimization ...

Collaborate with Data Scientists and Engineers to productionise models. Improve platform scalability, reliability, and automation. Key Skills Strong Python experience. MLOps tooling (MLflow, Kubeflow, SageMaker, or similar). Docker and Kubernetes. CI/CD tooling (GitHub Actions, GitLab CI, Azure DevOps). Cloud platforms (AWS, Azure, or GCP). ...

with serving patterns (e.g., REST APIs, batch inference, event-driven) Experience with orchestration tools (e.g., Airflow, Dagster) and cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI) Ability to influence decision-making regarding infrastructure and tooling, balancing 'build vs. buy' discussions Strong knowledge of Infrastructure as Code (Terraform ...

tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker, API protocols) is preferred but not required. Understanding model evaluation methods and metrics. Ability to operationalize non-technical ideas into relevant research designs, features ...

runbooks. Your Story5+ years' experience in ML Engineering, MLOps, or similar roles. Proficiency in Python. Experience with a managed machine learning platform such as Amazon SageMaker or an equivalent service. Practical knowledge of deploying and operating containerized workloads using Docker and Kubernetes. Experience developing or operating model-serving ...

Engineering depth: Strength in backend (Python, Node.js, Java), frontend (React, Angular), APIs (REST/GraphQL) Machine Learning: Foundations of MLflow, Weights & Biases, LoRA, PEFT, SageMaker, Vertex AI, AzureML, Kubeflow, Airflow, Prefect, TorchServe, Triton, vLLM, SHAP, LIME, pandas, Spark, SQLLLM tooling: Familiarity with LangChain, Semantic Kernel, prompt chaining, vector search ...

Strong Generative AI architecture experience, including LLM hosting, RAG, vector databases, prompt orchestration and guardrails. Knowledge of AI platform tooling such as Azure ML, Amazon SageMaker, MLflow, Kubeflow and Databricks . Ability to evaluate technologies and make evidence-based architectural decisions. Experience designing secure, scalable and cost-optimised ...

production Strong Python development skills Hands-on experience with LangGraph, LangChain, LlamaIndex, CrewAI or similar Experience with AWS, particularly Bedrock, Lambda, ECS, EKS or SageMaker Strong understanding of RAG, agentic AI and multi-agent architectures Experience with CI/CD, cloud infrastructure and application deployment Comfortable working directly with ...

offs. Real-time ML & reproducibility: A strong grasp of production inference patterns and reproducible environments (Docker, MLflow or equivalent). Cloud & tooling: AWS, plus SageMaker, Snowflake, Spark/Databricks and Kubernetes. Engineering mindset: A focus on reliability, maintainability and continuous improvement. ...

ethics An understanding of data safety in use of Large Language Models Knowledge and experience of either AWS or Azure: AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2) Azure (azure Open AI service, Cosmos DB) Python LangGraph Neo4j/cypher Other coding languages/frameworks e.g. Java/.Net ...

Python, Java, etc) in support of Investment Portfolio Management and Construction Utilizing AWS technologies such as Lambda, API Gateway, DynamoDB, S3, Glue, Redshift, EMR, Sagemaker, EKS/ECS. Working in a team with experienced software engineers to identify great projects and features that will help you grow in your ...

ethicsAn understanding of data safety in use of Large Language ModelsKnowledge and experience of either AWS or Azure: AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2)Azure (azure Open AI service, Cosmos DB)PythonLangGraphNeo4j/cypherOther coding languages/frameworks e.g. Java/.NetAI RAG (retrieval augmented generation)Graph RAGFew ...

engineering best practices , covering LLMOps, MLOps, CI/CD, automated evaluation, observability, security, performance and cost optimisation. Work extensively with AWS AI services , including Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions. What We Are Looking For: Proven experience as an Engineering Manager or Technical Lead with … agent frameworks such as LangGraph, Strands Agents or Claude Agent SDK, alongside interoperability standards including MCP and A2A. Strong AWS cloud engineering experience, particularly Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions, with Infrastructure as Code using AWS CDK or equivalent. Hands-on experience with LLMOps ...

opportunities across major UK and EMEA clients. Shape AWS-native agentic AI solutions that move clients from proof of concept to production, using Amazon Bedrock, AgentCore, agents, RAG, guardrails, orchestration, observability and operational controls. Architect complex cloud journeys including VMware/data-centre exit, mainframe and .NET modernisation … Migration Hub, Application Migration Service, AWS Database Migration Service, containers, serverless, managed databases and platform automation. Design production-ready AI/agentic solutions using Amazon Bedrock, AgentCore services, Knowledge Bases, vector/RAG patterns, Amazon Q/Quick where applicable, SageMaker AI, model evaluation and guardrails. Create ...

environment evolves, but typical tools include: Python for experimentation, modelling, and evaluation Weights & Biases (or equivalent) for experiment tracking AWS , including services such as SageMaker and Bedrock Internally supported AI development platforms and tooling This role is not suited to candidates who are dogmatic about specific tools . Adaptability ...

encounterThe environment evolves, but typical tools include: Python for experimentation, modelling, and evaluationWeights & Biases (or equivalent) for experiment trackingAWS, including services such as SageMaker and BedrockInternally supported AI development platforms and toolingThis role is not suited to candidates who are dogmatic about specific tools. Adaptability and outcome focus matter ...