ML Ops / Data Engineer
Tasks
- Build and maintain data pipelines
- Collaborate with platform and security teams
- Debug production issues
- Define system availability and latency targets
- Deploy and monitor ML models
- Design CI/CD pipelines for ML
- Ensure data quality and lineage
- Establish testing and validation practices
- Implement model monitoring
- Improve system robustness
- Manage experiment tracking
- Write production-grade Python
Perks/Benefits
- N/A
Skills/Tech-stack
CI/CD | Cloud infrastructure | Containerization | Data Engineering | Data Quality | ML pipelines | Model Deployment | Model Monitoring | Observability | Python | Workflow Orchestration
Education
Roles
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