Posted:-1 days ago|
Platform:
Work from Office
Full Time
Key Responsibilities :
- Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models.- Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability.- Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production.- Collaborate with data scientists to transition models from research and development into a production-ready state.- Automate the retraining and redeployment of models to maintain accuracy and adapt to new data.- Troubleshoot and resolve issues related to model deployment, performance, and infrastructure.- Stay updated on the latest MLOps tools, technologies, and best practices.
Required Qualifications :
- 3+ years of professional experience in MLOps, DevOps, or a similar role.
Preferred Qualifications :
- Experience with specific MLOps platforms like Kubeflow, MLflow, or SageMaker.- Knowledge of data engineering and building data pipelines.- A strong understanding of machine learning concepts and algorithms
Zorba Consulting India Pvt. Ltd.
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