Design, develop, train, fine-tune, and deploy AI/ML models for Communication Surveillance use cases.
Build advanced NLP solutions for analyzing structured and unstructured communication data.
Develop and optimize Large Language Model (LLM) and Generative AI-based solutions for surveillance and compliance applications.
Create scalable machine learning pipelines using Databricks Lakehouse Platform.
Manage model lifecycle using MLflow, including experiment tracking, model registry, deployment, monitoring, and version control.
Develop data preprocessing, feature engineering, model training, evaluation, and inference pipelines.
Work closely with business stakeholders, compliance teams, and domain experts to translate surveillance requirements into AI solutions.
Ensure model explainability, accuracy, robustness, and regulatory compliance.
Optimize model performance for production deployment and continuous improvement.
Collaborate with data engineers and platform teams to integrate AI solutions into enterprise applications.
Follow MLOps best practices for CI/CD, model governance, monitoring, and production support.
Document technical designs, model architecture, deployment processes, and operational procedures.
