1 to 25 of 44 Amazon SageMaker Jobs in the UK

develop, test, and support production-ready models using modern cloud technologies. The Role You will work primarily with Python, SQL, and AWS (including Amazon SageMaker) to: Extract, transform, and analyse data from AWS data platforms Perform exploratory data analysis and communicate insights clearly Build and evaluate baseline machine … learning models (classification & regression) Support model experimentation in Amazon SageMaker Unified Studio Contribute to model deployment, monitoring, and safe rollout practices Follow best practices in Git, code review, testing, and Agile delivery Support data governance, documentation, and privacy-by-design principles This role offers structured mentorship and exposure ...

monolithic EC2-centric AWS infrastructure by making use of containers and AWS managed services. Building AI applications using AWS’ suite of AI services including Amazon Bedrock. Using multimodal LLMs to build applications that supercharge existing businesses with AI. Building data processing pipelines on AWS. Writing Terraform or CloudFormation … following: Infrastructure as code (IaC) with Terraform and/or CloudFormation Containerization of Python, NodeJS, PHP and .NET applications using Docker on either Amazon ECS, Amazon EKS or AWS Elastic Beanstalk. Building applications or workloads with Foundational Models such as OpenAI’s GPT, Anthropic Claude, Amazon Bedrock ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (e.g. Azure Cognitive Services, AWS SageMaker, and/or GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (e.g. Jenkins, Docker, Kubernetes, and/ ...

Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/Bedrock, Google Vertex AI API-led architectures and microservices Security, governance, and responsible AI Frameworks ...

secure, and cost‐efficient deployments using Docker, Kubernetes (AKS/EKS/GKE), and Terraform/Bicep. Lead enterprise MLOps capabilities using Azure ML, SageMaker, Vertex AI, MLflow, and Kubeflow, integrated with CI/CD (GitHub Actions, Azure DevOps, Jenkins, Argo CD). Oversee observability and monitoring using Prometheus ...

expertise in services such as EC2, S3, RDS, Redshift, Glue, Lambda, Athena and Kinesis. Desirable: AI/Gen AI/ML services (e.g., SageMaker, Bedrock, Lex, Comprehend, Transcribe). Desirable: Experience with architecting and implementing data pipelines, data lakes, and data warehousing solutions optimised for GenAI workloads. Strong knowledge ...

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 ...

adapters), RAG , and evaluation (golden sets, BLEU/BERTScore/semantic similarity). Cloud : Azure (incl. Azure AI, OpenAI, Cognitive Services ), AWS (Bedrock/SageMaker), GCP (Vertex AI); containerization (Docker/Kubernetes) and service meshes. Data & Integration : SQL, NoSQL, data warehousing concepts (fact/dimension, SCD), ETL/ ...

related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/Airflow/Beam) Mobile and front-end web application development experience What We Offer ...

models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative AI initiatives using Hugging Face and open-source models Collaborate with data engineers, architects and stakeholders to deliver ...

orchestration tools like Kubeflow, Airflow, or Metaflow. Cloud Architecture: Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years ...

Generative AI models, LLMs, and agentic frameworks. Collaborate with stakeholders to define problem statements and solution approaches. Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. Ensure high-quality delivery and adherence to best practices ...

Generative AI models, LLMs, and agentic frameworks. •Collaborate with stakeholders to define problem statements and solution approaches. •Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines. •Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines. •Ensure high-quality delivery and adherence to best practices ...

serverless GenAI workflows for scalable, secure deployment. ML/LLM Engineering & LLMOps Work across AI/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector. Implement LLMOps/ ...

Machine Learning Architect/GenAI Architect Hands-on expertise with LLMs, RAG, LangChain, LangGraph, prompt engineering Strong cloud experience: Azure OpenAI, AWS Bedrock/SageMaker or GCP Vertex AI Experience with Kubernetes, Docker, microservices, API integration Strong knowledge of Python, MLOps, LLMOps, CI/CD, model monitoring Experience delivering ...

/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology). Familiarity with Docker/ec2, Terraform and CI/CD platform (Github Actions & Admin). Strong Data ...