MLOps Engineer (Machine Learning Platform & Cloud Infrastructure)
Tasks
- Automate machine learning workflows
- Automate model retraining processes
- Build scalable MLOps pipelines
- Deploy machine learning models to production
- Design cloud based machine learning infrastructure
- Implement infrastructure-as-code
- Implement model development deployment monitoring lifecycle management
- Maintain CI CD pipelines for machine learning
- Monitor infrastructure and model performance
- Optimize cloud resource utilization operational costs
Perks/Benefits
Skills/Tech-stack
AI Pipelines | AWS | Airflow | Amazon EKS | Azure AKS | CI/CD | Cloud platform | CloudFormation | Datadog | Docker | GitHub Actions | Google Cloud | Google Cloud Platform | Google GKE | Grafana | KServe | Kubeflow | Kubernetes | Linux | MLflow | Machine Learning | Microsoft Azure | Prometheus | Python | SageMaker | Sagemaker Pipelines | Terraform | Vertex AI | Vertex AI pipelines
Education
Bachelor of Engineering | Bachelor of Engineering in Computer Science | Bachelor of Science | Bachelor of Science in Computer Science
Roles
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