• Developed Python connectors and integrated databases using RESTful APIs in FastAPI, enabling seamless data exchange betweeninternal and external systems.• Designed and implemented webhooks for real-time notifications, integrating with third-party services to automate event-drivenupdates and enhance system monitoring.• Utilized Swagger for API design and documentation, streamlining integration processes and improving service communication.• Optimized database queries and API performance, ensuring enhanced scalability and reliability of the overall system.• Applied Test-Driven Development (TDD) to ensure code quality and robustness, writing unit tests for backend features.Technologies Used: Python, FastAPI, Swagger, RESTful APIs, Webhooks, SQL, NoSQL, Git, Test-Driven Development (TDD), Event-drivenarchitecture

• Developed an intelligent tutoring system using Rust and LLMs, leveraging OpenAI embeddings and RAG for adaptive learning.• Fine-tuned LLMs to deliver accurate, context-aware tutoring responses, enhancing the user experience with real-time engagement.• Architected the system with a focus on performance and scalability, utilizing Vertex AI and cloud-based data management solutions.• Integrated advanced Rust techniques and ML algorithms to dynamically generate tutoring content for individual user.• Optimized database queries and inference pipelines for improved content delivery using Vertex Database and Chroma .• Collaborated with cross-functional teams to refine the learning system’s performance and enhance the delivery of tutoring content.Technologies Used: Rust, LLMs, OpenAI Embeddings, RAG, Vertex Database, SQL, Chroma, Vertex AI , Machine Learning

•Developed and deployed machine learning models for predictive maintenance on IoT vending machines, improving optimization.• Analyzed large-scale sensor data using anomaly detection and supervised learning algorithms to mitigate risks.• Preprocessed and transformed raw data, extracting key features for model training and evaluation to improve model accuracy.• Collaborated with teams to deploy solutions in production, contributing to improved system reliability and uptime.• Utilized predictive analytics to identify critical faults, ensuring proactive maintenance and reducing machine downtime.Technologies Used: Python, Machine Learning, IoT, Anomaly Detection, Supervised Learning, Data Cleaning, Predictive Analytics, Sensor Data