Lead Architect - Mlops

Key Responsibilities: Machine Learning Pipeline Development Design and implement scalable ML pipelines using Azure ML, Databricks, and PySpark. Develop reusable ML workflow templates to streamline model training, validation, and deployment. Ensure pipeline efficiency, scalability, and reliability across environments. Model Development & Statistical Analysis Apply statistical techniques including hypothesis testing (T-Test, Z-Test), regression models (linear and logistic), and classification algorithms. Build ML models using frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, CNTK, and MXNet. Develop forecasting solutions using ARIMA, ARIMAX, and exponential smoothing techniques. Apply probabilistic models, graph-based models, and similarity metrics (Euclidean, Manhattan, Hamming). MLOps & CI/CD Implementation Build and maintain CI/CD pipelines using GitHub and GitHub Actions. Integrate code quality and security tools such as SonarQube. Automate deployment and monitoring of ML ...