ML Ops Support
Tasks
- Automate ML workflows
- Build requirements with technical and business teams
- Deploy offline models to production
- Design data pipelines
- Develop and deploy proof-of-concept ML systems
- Engineer ML infrastructure
- Ensure auditability and versioning for models
- Evaluate new technologies
- Implement CI/CD for ML models
- Improve production model performance maintainability reliability
- Maintain data security for ML models
- Manage model lifecycle and deployment
- Monitor ML models
- Retrain and scale ML models
- Track project progress
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | CI/CD | CloudFormation | Containerization | Data Preprocessing | Databricks | Docker | Feature Engineering | GCP | GitLab | Infrastructure as Code | Jenkins | Kubernetes | Machine Learning | Machine learning lifecycle | Machine learning monitoring | Model Deployment | Model versioning | Python | Terraform | “as-code”
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
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