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