Machine Learning Engineer
ZAR 660K-780K (estimate) Senior-level Full Time
Tasks
- Build and maintain deployment pipelines
- Containerize ML components
- Create documentation and run mentoring
- Create tooling for scalable ML development
- Deploy and optimize machine learning models
- Design production ML AI pipelines
- Implement DevOps practices for ML lifecycle
- Implement model versioning and validation
- Integrate version control
- Monitor models in production
- Orchestrate deployments
- Perform root cause analysis
- Provide AI ML solution architecture guidance
- Run model monitoring and data drift detection
- Set up model retraining workflows
- Troubleshoot infrastructure and application issues
Perks/Benefits
Skills/Tech-stack
AWS | Amazon ECS | Amazon EKS | Amazon SageMaker | Artificial Intelligence | Azure | CI/CD | Cloud Native | Cloud Security | Cloud platform | CloudFormation | Container Orchestration | Dask | Data Drift | Data Drift Detection | Debugging | Distributed Computing | Docker | Drift Detection | GitOps | Google Cloud | Google Cloud Platform | Google Kubernetes | Google Kubernetes Engine | Infrastructure as Code | Kubeflow | Kubernetes | Kubernetes Engine | MLOps | MLflow | Machine Learning | Model Monitoring | Networking Fundamentals | Pulumi | Ray | Spark | Terraform | Vertex AI | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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