About this role
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
Applications are read by our talent team, usually within two working days.
If you look like a fit we will call you, and you will hear from us either way.