Ml Aws
23 hours ago
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
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