Cloud AI/ML Engineer
Tasks
- Build ML infrastructure on AWS
- Build infrastructure as code with Terraform
- Deploy and serve ML models in production
- Document ML systems and runbooks
- Drive GenAI and agentic AI workflows with safety controls
- Implement ML model governance and security controls
- Implement MLOps pipelines
- Monitor model performance and data drift
- Set up CI CD pipelines for ML workflows
- Troubleshoot ML and infrastructure issues
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Step Functions | Alerting | Amazon Bedrock | Amazon ECR | Amazon S3 | Amazon SageMaker | CI/CD | Data Drift | Data Drift Detection | Data Quality | Docker | Drift Detection | ECS | ELT | ETL | Elastic Kubernetes | Elastic Kubernetes Service | Feature Engineering | Git | Kubeflow | Kubernetes | Kubernetes Service | Lambda | MLflow | Model Governance | Model Registry | Model versioning | Monitoring | PyTorch | Python | Retraining | Sagemaker Pipelines | Scikit-learn | Step Functions | TensorFlow | Terraform | XGBoost
Education
N/A
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