## Job highlights
- 2-5 years experience with MLOps, AWS cloud services, strong Python skills, expertise in MLflow, Terraform, Kubernetes
- Design and maintain MLOps pipelines, deploy ML models on AWS, build CI/CD pipelines, automate infrastructure, containerize apps, monitor models and cloud resources, collaborate with cross-functional teams 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
- Solid Python Development
- Shell Scripting (Bash)
- API Development & Integration

📌 MLOps + AWS devops (Bengaluru)
🏢 Infosys
📍 Bengaluru