5 of 5 Remote/Hybrid Amazon SageMaker Jobs in London

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 ...

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 ...

pipelines for training, validation and deployment. Implementing CI/CD workflows for machine learning and maintaining reliable ML endpoints. Working heavily with AWS, including SageMaker, to deliver robust, secure and scalable ML infrastructure. Applying strong engineering standards across cloud, DevOps and automation practices. Contributing to computer vision and broader ...

machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration skills, and a results-driven mindset Role responsibilities: Build … tune, and maintain predictive and ML models using AWS SageMaker Analyse large datasets and perform feature engineering to improve model performance Run experiments, test hypotheses, and optimise models for accuracy and value Monitor model performance and manage retraining over time Collaborate with Data Engineers, BI Developers, and Analysts ...