ML pipeline creation, drift monitoring and control
Automating CI / CD pipelines to account for data, code, and model changes
Develop and deploy CI / CD-based automated ML application pipelines (collection, processing, cleaning, transformation, etc.) along with the CT component for a continuous feedback loop for re-training.
Implement model evaluation and model + data validation tools / techniques such as schema validation, evaluation metrics, etc.
Querying and working with databases, testing ML models, Git and version control, and frameworks like Flask, and FastAPI.
Develop and maintain schedulers to orchestrate and schedule various data processing and machine learning tasks.
Currently exploring triggers based on data changes, model performance degradation, or predefined schedules to initiate retraining workflow.
Regards,
Manvendra Singh
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Mlops Engineer • hyderabad, India
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