I am a highly motivated, passionate, and self-driven professional with 6+ years of industry experience in Analytics and Computer Science. I have excellent communication skills; leadership skills, and I am very enthusiastic about solving problems. I have a proven track record of 4+ years of experience with projects in Machine Learning Engineering, Natural Language Processing, and Deep Learning built with industry standards. My work involves:1. Data modeling and collecting data in a data warehouse inside AWS from multiple data sources and performed data extraction with ETL.2. Completing data acquisition, data analysis, mining, data visualization, and quantitative research to come up with use cases.3. Design and implement functional data flow in the data engineering pipeline between databases and backend systems.4. Running Machine Learning Experiments and have hands-on experience with Libraries such as PyTorch, TensorFlow.5. Investigate ML Algorithm behavior and design / implement Custom Machine Learning / Neural Network model architectures.6. Training ML models, evaluating model performance, tuning hyperparameters, and validating using useful metrics and statistical methods.7. Optimizing Machine Learning Solutions for Performance, Scalability, and understanding system reliability.8. Model inferencing would be dealt with either Scala or Rust or Python, and the model transfer between languages would be handled through the ONNX platform.9. Serving the Machine Learning models as either web services API ( using Microservices such as flask/pyramid) or as Online Scoring using Kafka and Spark Streaming. 11. Debugging and Deploying Machine Learning / Deep Learning models into production using spark for batch prediction and using Kafka for real-time prediction.12. Monitoring machine learning models to understand the changes in models predictive performance in real-time (Model Drift).13. Scalability and Fault Tolerance is achieved with Kubernetes and Docker.14. The machine learning life cycle is maintained with MLFlow.15. Publishing major Python and Data Science packages for the organization code repository.16. Performing market research and strategy using AI tools, develop the documentation, collaborate and write reports/publications, and deliver PowerPoint presentations and keynote presentations to prepare CEO for multiple speaking engagements.