MLOps Engineer

Job Description:

We are seeking an experienced MLOps Engineer with strong expertise in deploying managing and optimizing machine learning workloads in production environments

This role is primarily focused on MLOps 60 supported by AWS Cloud 25 and DevOps 15 capabilities

The ideal candidate will have hands on ownership of the end to end ML lifecycle including model training deployment monitoring automation performance optimization and retraining

Strong experience with AWS services CI CD pipelines containerization infrastructure automation and production grade ML platforms is essential

This is not a generic DevOps role candidates must demonstrate proven experience in operationalizing and maintaining ML models at scale in cloud environments

Key Responsibilities:

5 yrs DevOps Cloud MLOps experience Python for scripting and automation

Strong with Jenkins Git Docker EKS troubleshooting

AWS SageMaker Lambda S3 ECS IAM RDS infra creation

IaC CloudFormation CFT and Terraform

MLOps build operate ML pipelines deploying to SageMaker Databricks or Lambda

Technical Requirements:

SageMaker

MLflow

Kubeflow

Databricks

MLOps

Model Deployment

Model Monitoring

Model Retraining

Feature Store

CI CD for ML

Training Pipelines

Inference Pipelines

Drift Detection

Docker

Kubernetes EKS

Terraform

CloudFormation

AWS Lambda

Python Automation

Preferred Skills:

Technology->AI-Data science->PYTHON,Technology->AI-Physical AI-IOT->IOT Analytics - Machine Learning