- Model Development and Deployment:
- Design, develop, and implement machine learning models for various applications (e.g., classification, regression, natural language processing, computer vision).
- Deploy and maintain machine learning models in production environments.
- Optimize model performance and efficiency through feature engineering, hyperparameter tuning, and model selection.
- Build and maintain scalable machine learning pipelines.
- Data Engineering and Management:
- Work with large datasets, including data cleaning, preprocessing, and feature extraction.
- Develop and maintain data pipelines for data ingestion, transformation, and storage.
- Ensure data quality and consistency.