- Design, deploy, and maintain scalable cloud-based infrastructure on AWS using DevOps practices.
- Collaborate with cross-functional teams to identify areas for improvement in the development process and implement automated solutions.
- Develop and execute deployment plans to ensure smooth rollout of applications across multiple environments.
- Troubleshoot issues related to application performance, availability, and security.
Job Requirements :
- 5-9 years of experience in DevOps engineering with expertise in AWS.
- Design, deploy, and support scalable AWS-based MLOps and data platforms.
- Manage and optimize AWS services including SageMaker, EKS, Lambda, S3, Glue, Athena, and Redshift.
- Support ML model deployment, lifecycle management, model monitoring, and operational governance.
- Collaborate with data scientists and engineering teams to operationalize ML workflows and automate model delivery pipelines.
- Robust understanding of CI/CD pipelines, containerization (e.g., Docker), orchestration (e.g., Kubernetes).
- Experience with monitoring tools such as Prometheus, Grafana; logging analysis tools like ELK Stack.