Manager

Job Title: Senior DevOps & MLOps Engineer (AWS | CI/CD | Python/Bash)

Experience

Employment Type

Job Summary

Senior DevOps & MLOps Engineer

AWS cloud infrastructure

CI/CD pipelines

MLOps practices

scripting (Python/Bash)

Key Responsibilities

• Design, implement, and maintain cloud-native infrastructure on AWS, including compute, networking, and security.
• Develop and manage CI/CD pipelines using tools like GitLab CI/CD, Jenkins, CodePipeline, or GitHub Actions.
• Set up and manage end-to-end MLOps workflows, including model training, versioning, deployment, monitoring, and rollback.
• Create and manage infrastructure as code (IaC) using Terraform, CloudFormation, or AWS CDK.
• Implement containerized environments using Docker and Kubernetes (EKS preferred).
• Automate repetitive tasks and operational processes using Python, Shell, or Bash scripts.
• Collaborate with ML and application teams to integrate models into production workflows.
• Monitor system performance and implement robust logging, alerting, and monitoring using CloudWatch, Prometheus, Grafana, or ELK.
• Ensure security, compliance, and cost-efficiency of cloud infrastructure.
• Troubleshoot and resolve issues in dev/test/prod environments.
  

Required Skills & Qualifications

• 8-11 years of total experience in DevOps, Cloud Engineering, or MLOps.
• Strong AWS expertise (EC2, S3, Lambda, IAM, VPC, RDS, EKS, SageMaker, etc.).
• Proven experience in building and maintaining CI/CD pipelines.
• Deep understanding of MLOps principles and tools like MLflow, Kubeflow, or SageMaker Pipelines.
• Proficient in Python and Bash scripting.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Familiarity with infrastructure as code (Terraform, CloudFormation, CDK).
• Good understanding of DevSecOps and security best practices.
• Hands-on with monitoring/logging tools (CloudWatch, ELK Stack, Prometheus, etc.).
• Experience in working in Agile/Scrum environments.
  

Preferred Qualifications

• AWS Certification (Solutions Architect, DevOps Engineer, or equivalent).
• Exposure to DataOps, Data Engineering, or Feature Store implementations.
• Experience with on-prem to cloud migration.
• Knowledge of serverless architectures.