ML Ops & Observability Engineer
IND - Chennai Office, India
INR 2500K-4500K (estimate) Senior-level Full Time
Tasks
- Add automated ML testing to pipelines
- Build Prometheus metrics dashboards
- Coach engineers on MLOps and observability
- Conduct post-incident reviews
- Define SLOs and alerts for ML services
- Define data quality checks
- Deploy machine learning models
- Design MLOps platforms
- Detect data drift
- Enable responsible AI operations
- Implement CI/CD pipelines for ML
- Implement observability with OpenTelemetry
- Improve MLOps maturity with SRE practices
- Lead engineering runbooks and documentation
- Lead incident response for ML outages
- Manage model versioning and rollback
- Monitor model performance
- Package models for production
- Perform performance and scalability testing
- Run model validation and regression testing
- Set up logging with ELK
- Support security and access validation
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Access Control | Azure | Bash | CI/CD | Data Drift | Data Drift Detection | DevSecOps | Docker | Drift Detection | ELK | Feature Store | GitHub Actions | Grafana | Kubeflow | Kubernetes | MLflow | Model Monitoring | Model Registry | Observability | OpenTelemetry | Prometheus | Python | SLO | SQL | SRE | Secrets management
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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