Sai Teja

I’ve been building AI/ML and IoT projects that connect sensors to actionable alerts—like my child safety tracker using Arduino GPS+GSM and smart pest detection with ESP32-CAM.

During my AWS Academy data engineering internship, I set up EC2 instances and S3 buckets with IAM roles, used CloudWatch for monitoring and alerts, and built end-to-end AWS data pipelines with Python.

On the AI side, I created an AI-based stock prediction system that combines stock data with sentiment signals using XGBoost and LSTM, plus tools like VADER and FinBERT, with a live Streamlit dashboard.

Right now, I’m working as a Data Annotation Intern with TAO Digital, quality-checking labeled text, image, and audio datasets to keep annotation accuracy consistent for downstream model training.