MLOps & AI Platform Engineer
Tasks
- Automate machine learning pipelines
- Build and maintain MLOps platforms
- Create CI/CD pipelines for AI workloads
- Deploy and manage ML workloads on Kubernetes
- Ensure security, scalability, and reliability
- Implement infrastructure as code with Terraform
- Implement model experiment tracking
- Manage model versioning and registry
- Monitor platform health and model performance
- Troubleshoot production issues and optimize performance
Perks/Benefits
- N/A
Skills/Tech-stack
AI Pipelines | AKS | Apache Airflow | Bash | CI/CD | Docker | EKS | GKE | GitHub Actions | Infrastructure as Code | Kubeflow | Kubernetes | MLflow | Prometheus | Python | Sagemaker Pipelines | Terraform | Vertex AI | Vertex AI pipelines | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Platform Engineer | Engineer | MLOps Engineer | Platform Engineer
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