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About the role
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 Model experimentation: Jupyter Notebook, Google Colab, Kaggle
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