- Model Deployment: Deploy and manage machine learning models in production using tools like MLflow Kubeflow or AWS SageMaker ensuring scalability low latency.
- Monitoring Observability Build and maintain dashboards using Grafana Prometheus Kibana to track real-time model health e.g., accuracy latency historical trends
- Data Drift Detection Implement drift detection pipelines using tools like Evidently AI Alibi Detect to identify shifts in data distributions trigger alerts retraining
Artificial Intelligence Integration Engineer - Arlington - Sev1Tech
Description
Job Responsibilities
The Artificial Intelligence Integration Engineer will design, implement, and maintain end-to-end machine learning pipelines focusing on automating model deployment.
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