8 of 8 Remote Amazon SageMaker Jobs in Manchester

and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK, CloudFormation to provision and manage cloud environments. Build and maintain CI/CD pipelines using GitHub Actions, AWS CodePipeline …/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services (AWS) – SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS. Proficiency in Infrastructure-as-Code using AWS CDK or CloudFormation. Experience implementing and scaling MLOps … workflows with tools such as MLflow, SageMaker Pipelines. Proven experience building, containerising, and deploying using Docker and Kubernetes. Hands-on experience with CI/CD tools (GitHub Actions, CodePipeline, Jenkins) and version control using Git/GitHub. Strong understanding of DevOps concepts including blue/green deployments, canary releases, rollback strategies, and infrastructure automation. Familiarity with security and compliance More ❯

Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large language models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related services. Guide the use of Infrastructure-as-Code (IaC) practices with AWS CDK and CloudFormation to provision and manage secure and maintainable cloud environments. … experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud-native environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC, ECS/EKS, with a strong command of cloud solution architecture. Advanced proficiency in Infrastructure-as-Code practices using AWS CDK, CloudFormation, or … Terraform in production environments. Proven track record designing and operationalised end-to-end MLOps pipelines with tools such as MLflow, SageMaker Pipelines, or equivalent frameworks. Extensive experience building and operating containerised applications using Docker and Kubernetes, including production-grade orchestration and monitoring. Deep experience with CI/CD best practices with hands-on expertise in GitHub Actions, Jenkins, and More ❯

of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review). Machine/Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). An understanding of Language Models, using and training/fine-tuning and a familiarity with industry-standard LM families. More ❯

classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor's degree (master's or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field More ❯

classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor’s degree (master’s or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field More ❯

models into production. You'll be fluent in Python - writing readable, testable, and maintainable code comes naturally to you. You'll be comfortable with cloud-based tools like AWS SageMaker and Lambda, and you'll know your way around Git, SQL, and common Python data science libraries (like pandas/polars, scikit-learn, xgboost/lightGBM, and TensorFlow/ More ❯

just file handling). Understanding and experience of Data Governance frameworks and implementation. Exposure to CI/CD pipelines and source control for reports and analytics. Bonus: Familiarity with SageMaker or similar ML/predictive analytics platforms. We're looking for someone who: Thinks like a data user, not just a data builder with a strong sense of how More ❯

just file handling). Understanding and experience of Data Governance frameworks and implementation. Exposure to CI/CD pipelines and source control for reports and analytics. Bonus: Familiarity with SageMaker or similar ML/predictive analytics platforms. We're looking for someone who: Thinks like a data user, not just a data builder with a strong sense of how More ❯