Sagemaker DevOps Engineer
Core
Design, automate, and maintain cloud-based MLOps solutions for enterprise-scale machine learning infrastructure.
Role type
Senior Sagemaker DevOps Engineer
Builds
Scalable AWS SageMaker environments, CI/CD pipelines, and automated model deployment workflows.
Domain
Cloud Infrastructure / Machine Learning Operations (MLOps)
Deliverable
production ML models | infrastructure
Required skills
AWS services, Python, Amazon SageMaker, DevOps automation, CI/CD principles, infrastructure automation
Preferred skills
Jenkins pipelines, MLOps workflows
Technologies
AWS, SageMaker, Python, Jenkins
Responsibilities
Design and build enterprise-grade AWS SageMaker environments; Develop DevOps automation for SageMaker Unified Studio; Configure and maintain SageMaker lifecycle configurations; Build and optimize CI/CD pipelines for custom Docker images and ML workloads; Develop monitoring, alerting, and cost-control mechanisms; Implement MLOps automation for model deployment; Collaborate with engineering teams to improve cloud architecture.
Seniority
Senior, hands-on IC
