• Prepare, deploy, monitor, and support all AI/ML models in production. 
• Design and evolve the team's MLOps platforms and processes. 
• Experienced with different aspects of ML Lifecycle Activities: 
• Data collection and preparation 
• Feature engineering 
• Model development , evaluation and deployment
• Model monitoring and maintenance 
• Experienced with popular Tools for Model Monitoring, Deployment, Governance, Retraining, and Experimentation: 
• Model monitoring: Prometheus, Grafana, Datadog, New Relic 
• Model deployment: TensorFlow Serving, TorchServe, Amazon SageMaker, Google Cloud AI Platform 
• Model governance: ModelDB, MLflow, Neptune.ai 
• Model retraining: MLflow, AWS SageMaker, Google Cloud AI Platform 

Same