ML Platform Engineer
Tasks
- Build and maintain MLOps automation end to end
- Build and maintain data pipelines
- Build and maintain training and experimentation infrastructure
- Contribute to documentation and platform standards
- Design and maintain feature store
- Enforce secure data handling and compliance
- Expose governed datasets features and APIs
- Implement and operate model serving infrastructure
- Implement observability for ML systems
Perks/Benefits
- Dental care
- Free coffee
- Free drinks
- Free snacks
- Health insurance
- Learning courses access
- Meal vouchers
- Multisport card
- Optical glasses
- Paid leave
- Performance bonuses
- Promotions
- Public transport pass
- Teambuilding activities
- Training budget
Skills/Tech-stack
AWS | Access Control | Airflow | Alerting | Audit Logging | Azure | Bias monitoring | BigQuery | CI/CD | Cloud Build | Composer | Containerization | Dagster | Data Drift | Data Drift Detection | Data Pipelines | Data Quality | Docker | Drift Detection | Experiment tracking | Feature Engineering | Feature Store | GitHub Actions | Google Cloud | Incident Response | MLOps | MLflow | Model Monitoring | Model Registry | Pipeline Orchestration | Python | SQL | Spark | Terraform | Vertex AI
Education
Roles
Engineer | ML Platform Engineer | MLOps Engineer | Platform Engineer
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