MLOps + AWS devops

Role: MLOps + AWS DevOps Engineer
Experience: 2-5 Years
Employment Type: Full-Time

Job Summary

We are looking for a talented MLOps + AWS DevOps Engineer with strong Python skills and hands-on experience in building, deploying, and maintaining machine learning solutions on AWS cloud infrastructure. The ideal candidate should have expertise in MLOps, DevOps automation, cloud-native technologies, CI/CD pipelines, and containerized deployments.

Key Responsibilities

• Design, develop, and maintain end-to-end MLOps pipelines for model training, testing, deployment, and monitoring.
• Deploy and manage ML models using AWS services such as SageMaker, EKS, ECS, Lambda, and S3.
• Build and maintain CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI/CD, or similar tools.
• Automate infrastructure provisioning using Terraform, CloudFormation, or other IaC tools.
• Develop automation scripts and tools using Python.
• Containerize applications using Docker and orchestrate workloads using Kubernetes/EKS.
• Monitor cloud resources, applications, and ML models using CloudWatch, Prometheus, and Grafana.
• Implement model versioning, data versioning, and experiment tracking using MLflow or similar tools.
• Collaborate with Data Scientists, Data Engineers, and Software Engineers to operationalize ML solutions.
• Ensure security, scalability, reliability, and cost optimization of cloud infrastructure.

Required Skills

MLOps

• Machine Learning Model Deployment
• ML Pipelines & Workflow Automation
• MLflow / Kubeflow
• Model Monitoring & Retraining
• Feature Store Concepts
• Model Versioning

AWS Cloud

• EC2, S3, IAM
• VPC, Route53
• Lambda
• ECS/EKS
• CloudWatch
• RDS
• SageMaker
• Step Functions

DevOps

• CI/CD Pipelines
• Jenkins / GitHub Actions / GitLab CI
• Terraform / CloudFormation
• Docker
• Kubernetes
• Linux Administration

Programming

• Strong Python Development
• Shell Scripting (Bash)
• API Development & Integration