ML AWS

**Machine Learning Engineer – AWS Workflow Specialist \- keen to get a get a really good MLE.** **Machine Learning Engineer with experience in designing, building, and deploying end\-to\-end ML workflows on AWS, utilising SageMaker Pipelines and SageMaker Endpoints.** **Deep understanding of core AWS services including S3, KMS , Lambda , Secrets Manager** **and CI/CD tools such as CodeBuild and CodePipeline to automate deployments.** **Skilled in orchestrating complex workflows with Airflow and integrating streaming data from Kafka. Short Description of the Job** **Deploy, automate, maintain and monitor machine learning models and algorithms to ensure that that they work effectively in a production environment.** **Key Responsibilities** **Understand the needs of business stakeholders, and how machine learning solutions can meet those needs in order to support the achievement of business strategy** **Work collaboratively with colleagues to productionise machine learning models including pipeline design and development, testing and deployment ensuring that the original intent and knowledge is carried over to production** **Create frameworks to ensure robust monitoring of machine learning models within production environment ensuring models are delivering expected quality and performance, understanding and addressing any shortfalls for example through retraining** **Work in an agile way within multi\-disciplinary data and analytics teams to achieve agree**