• Design, develop, train, and fine-tune machine learning models, including custom and pre-trained models on Google Cloud Vertex AI and Document AI. • Build and manage custom Document AI processors such as Custom Document Splitter, Custom Document Classifier, and Custom Document Extractor. • Work with pre-trained Document AI processors and customize them for business-specific document understanding tasks. • Develop and deploy ML solutions using GCP services like Cloud Functions, Cloud Run, Firestore, Cloud SQL, Cloud Storage, and BigQuery. • Design and implement data preprocessing pipelines for large-scale, unstructured, and semi-structured data. • Integrate ML models into production systems via secure and scalable APIs. • Evaluate model performance using standard ML metrics, perform model validation, and optimize for accuracy, latency, and efficiency. • Collaborate with cross-functional teams (Data Engineers, Software Developers, and Product Teams) to ensure seamless model integration and delivery. • Troubleshoot and debug ML pipelines, training jobs, and model deployment issues. • Maintain proper version control of code, models, and configurations using Git/GitHub. • Follow best practices for ML lifecycle management, testing, and documentation.