SAI DHEERAJ REDDY MOLLALA

• Proficient in Python, Java, and JavaScript, with experience developing AI-driven apps using frameworks such as Flask, Django, Spring and LangChain.
• Skilled in machine learning, with practical expertise in support vector machines (SVM), random forests, CNNs, and LLM fine-tuning.
• Extensive expertise creating real-time data visualization dashboards and full-stack online apps that provide seamless user experiences.
• Led data-driven initiatives with Apache Spark and Mllib and created AI-powered bots such as GroceryBot with RAG and ReAct agents.
• Experienced with cloud technologies such as AWS, Docker, and Google Cloud for deployment and production scalability.
• Capable of managing big datasets, improving speed, and integrating powerful back-end functions.
• Proven ability to work with cross-functional teams to provide high-quality software solutions while promoting creativity and efficiency in all projects.

Grocery Bot -Al Conversational Bot for Grocery Shopping.,

 Role: Al Developer, 

• Developed a conversational AI bot for grocery shopping, offering meal suggestions, cooking instructions, and product recommendations.
• Utilized Retrieval Augmented Generation (RAG) for accurate recipe and product data.
• Implemented a ReAct-based agent on LangChain for dynamic database interaction.
• Integrated Faiss vector database for catalog management and Vertex AI for large-scale data handling.
• Designed a scalable system architecture using NoSQL databases for recipe queries and product suggestions.

Environment: Google Colab 

Real-Time Data Analytics Platform, 

Role: AWS Cloud Engineer, 

• Designed and developed a real-time data analytics platform using AWS serverless architecture.,
• Created Python-based AWS Lambda functions to process data from multiple sources.,
• Automated ETL processes using AWS Glue, integrating structured data into DynamoDB.,
• Implemented a data lake architecture with S3 and Athena, improving data retrieval efficiency.,
• Integrated RESTful APIs using API Gateway, securing them with AWS Cognito., Orchestrated workflows with Step Functions to streamline processes and reduce execution time.,
• Monitored performance using CloudWatch, setting up custom metrics and alarms.., Environment: AWS Lambda, Python, Serverless Framework

Detection of Cyber Attacks Using Machine learning,

 Role: Python Developer, 

• implemented Support Vector Machine (SVM), Random Forest (RF), and Convolutional Neural Network (CNN) algorithms for cyber-attack detection, showcasing a diverse skill set in machine learning.,
• Leveraged Python as the primary programming language for both machine learning model development and webpage implementation.,

Environment: Jupyter Notebook