Job Summary

We are looking for experienced AWS DevOps Engineers who are interested in transitioning into MLOps. This opportunity is ideal for professionals with a strong AWS DevOps background who are eager to work on Machine Learning Operations (MLOps) for a leading Life Sciences client.

You will collaborate with Data Scientists, ML Engineers, and Cloud teams to automate ML model deployment, monitoring, and lifecycle management while leveraging AWS cloud technologies and DevOps best practices. Key Responsibilities

Design, develop, and maintain scalable MLOps pipelines on AWS.

Automate deployment, monitoring, and lifecycle management of machine learning models.

Build and manage CI/CD pipelines for ML workloads.

Implement Infrastructure as Code (IaC) using Terraform or CloudFormation.

Containerize applications using Docker and orchestrate deployments using Kubernetes/EKS.

Monitor cloud infrastructure, applications, and ML model performance.

Collaborate with Data Scientists and ML Engineers to operationalize ML models.

Ensure cloud security, governance, and operational best practices.

Troubleshoot production issues and optimize AWS environments.

Required Skills

6+ years of experience in AWS Cloud & DevOps.





Robust hands-on experience with AWS services including:

EC2

S3

IAM

VPC

Lambda

CloudWatch

ECS/EKS

RDS

Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

Hands-on experience with Docker and Kubernetes.

Strong scripting skills in Python, Bash, or Shell.

Experience with Infrastructure as Code (Terraform or CloudFormation).

Good understanding of monitoring, logging, and cloud operations.

Experience working in Agile environments.

Preferred Skills

Exposure to AWS SageMaker or other MLOps platforms.

Understanding of Machine Learning model lifecycle and deployment.

Familiarity with MLflow, Kubeflow, or similar MLOps tools.

Experience in the Life Sciences or Healthcare domain is preferred.

Ideal Candidate

AWS DevOps Engineer looking to build a career in MLOps.

Strong automation and cloud engineering mindset.

Excellent communication and problem-solving skills.

Ability to work effectively with cross-functional teams.

Job Details

Location: Preferred Hyderabad OR Anywhere in India

Experience: 6+ Years

Domain: Life Sciences

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