MLOps Engineer
USD 130K-195K (estimate) Senior-level Full Time
Tasks
- Automate model updates testing and deployment with CI CD
- Build machine learning pipelines
- Deploy machine learning models in production
- Detect data drift and trigger alerts
- Document pipelines and monitoring processes
- Implement security and compliance controls for AI systems
- Maintain dashboards and real time and historical insights
- Monitor model health and performance
- Optimize models for production performance and resource usage
- Set up centralized logging and tracing
Perks/Benefits
- N/A
Skills/Tech-stack
AUC | AWS SageMaker | Access Control | Adversarial Attacks | Adversarial Robustness | Adversarial Robustness Toolbox | Alibi Detect | Azure Machine Learning | CI/CD | Datadog | Docker | ELK Stack | Encryption | Evidently AI | GDPR | GitHub Actions | Grafana | HIPAA | InfluxDB | Jenkins | KS test | Kibana | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | OpenTelemetry | PSI | Plotly | Precisión | Prometheus | Pruning | Python | Quantization | Recall | SQL | Seaborn | Time Series | TimescaleDB
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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