Ml Aws
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Monthly Salary:
Posted on:
20 hours ago
Vacancies:
1 Vacancy
Job Summary
| 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 |
About Company
At Virtusa, we are builders, makers, and doers. Digital engineering is in our DNA. It’s at the heart of everything we do.
