DevOps Engineer – MLOps / AWS (Contract)

Job Summary

We are looking for an experienced DevOps Engineer with strong AWS, Infrastructure\-as\-Code, containerization, and CI/CD expertise to support an ML/AI infrastructure pipeline. The ideal candidate will be responsible for building reliable, reproducible, and portable infrastructure for LoRA model training, adapter packaging, and model deployment.

Key Responsibilities

• Provision and manage GPU\-based training and inference infrastructure using AWS services.
• Implement Infrastructure\-as\-Code (IaC) using Terraform or AWS CloudFormation.
• Build and maintain CI/CD pipelines for model training, adapter packaging, and deployment.
• Containerize training and model\-serving applications using Docker.
• Manage container orchestration using Kubernetes.
• Configure monitoring, logging, observability, and cost optimization for GPU workloads.
• Ensure reproducibility and portability of ML pipelines across different environments.
• Manage AWS IAM permissions, S3 storage, EC2 GPU instances, and SageMaker infrastructure.
• Collaborate with ML engineers to streamline model training and deployment workflows.

Required Skills

• 6\+ years of experience in DevOps, Cloud Infrastructure, or related roles.
• Strong hands\-on experience with AWS, particularly SageMaker, EC2 GPU instances, IAM, and S3\.
• Expertise in Terraform or CloudFormation.
• Strong experience with Docker and Kubernetes.
• Experience building CI/CD pipelines using GitHub Actions, GitLab CI, or similar tools.
• Knowledge of MLOps workflows and ML model deployment.
• Experience with monitoring and observability tools.
• Understanding of GPU compute orchestration, infrastructure automation, and cloud cost optimization.

Additional Details

• Long\-term contract opportunity with a possibility of extension.
• Remote/offshore collaboration.
• Candidates should have strong communication and collaboration skills.
• Immediate availability or short notice period is preferred.

Pay: ₹90,000\.00 \- ₹100,000\.00 per month

Work Location: Remote