26 to 50 of 159 Amazon SageMaker Jobs in the UK

. 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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 . ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

APIs, API Gateway, and Spring Boot for application integrations AI/ML Integration: Implementing AI/ML integration layers connecting applications to services like Amazon Bedrock, SageMaker, and OpenAI APIs for intelligent features Event-Driven Architecture: Building event-driven architectures using Kafka/MSK, AWS EventBridge … work status. We are unfortunately unable to offer sponsorship Desirable AWS serverless services: Lambda, API Gateway, DynamoDB, EventBridge, Step Functions AI/ML platforms: Amazon Bedrock, SageMaker, OpenAI APIs, or similar services Event-driven architecture: Messaging systems and asynchronous processing (Kafka/SQS) Infrastructure as Code: CloudFormation ...

Turn machine learning engineer/scientist models into production services meeting latency, cost, and reliability targets • Build and maintain SageMaker training, processing, and inference workloads • Build pipelines that orchestrate SageMaker workloads • Make training runs reproducible and configuration-driven so results can be rebuilt from code • Build monitoring … Deep hands-on PyTorch experience; TensorFlow welcome Experience with Hugging Face Transformers, timm, scikit-learn, NumPy, pandas, and OpenCV Production experience on AWS, specifically Amazon SageMaker, including training and processing jobs, pipelines, model registry, and endpoints Practical MLOps experience with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training ...

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 ...

Notebooks Strong understanding of predictive modelling and machine learning techniques Experience with NLP and Large Language Models (LLMs) Familiarity with AWS services, including S3, SageMaker and Lambda Experience or knowledge of Microsoft Fabric Understanding of the machine learning model development and deployment lifecycle Strong analytical and problem-solving abilities ...

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 ...

Bedrock Experience with Kubernetes, CI or CD, infrastructure as code, and automation tools Familiarity with AI or ML platforms such as Databricks, SageMaker, or MLflow Exposure to hybrid cloud architectures and large scale data processing ecosystems Knowledge of enterprise data platforms, observability, and cost management tooling Leadership Expectations ...