AWS Machine Learning Infrastructure Specialist

1 week ago

agra, India beBeeMachineLearning Full time

As an MLOps Engineer, you will design, deploy and maintain robust machine learning pipelines using AWS SageMaker. Key responsibilities include building, deploying and maintaining ML models, automating CI/CD workflows, implementing model monitoring and logging, and creating secure, scalable, cost-optimized AWS environments.Key ResponsibilitiesBuild, deploy and maintain ML models using AWS SageMaker Pipelines, Endpoints and Model Registry.Develop automated CI/CD workflows using CodePipeline, CodeBuild or GitHub Actions.Implement model monitoring, logging and drift detection using CloudWatch and SageMaker Model Monitor.Create and maintain infrastructure using Terraform or CloudFormation.Manage secure, scalable, cost-optimized AWS environments using IAM, VPC and networking.Collaborate with data scientists, cloud engineering teams and solution architects.Troubleshoot issues in high-availability production ML setups.Required Skills and Qualifications4–8 years total experience in MLOps, ML Engineering.Hands-on experience with SageMaker in enterprise-scale environments.Strong Python skills and familiarity with ML frameworks.Experience with Docker, Kubernetes, EKS preferred.Experience building CI/CD pipelines.Deep practical knowledge of the AWS ecosystem.

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