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-AI Engineering->MLOps,Technology->AI-Data science->Machine Learning,Technology->Devops->Ansible,Technology->OpenSystem->Python - OpenSystem