AI/ML Engineer at Airbnb

Engineered ETL pipelines with PySpark, Airflow, and Kafka to process 50M+ booking and transaction records daily, streamlining analytics workflows and cutting reporting latency by 18 staff hours per week. Developed and trained predictive models using TensorFlow, PyTorch, and Scikit-learn to forecast seasonal occupancy, enabling revenue optimization strategies that generated $25M+ in booking value across global regions. Designed deep learning pipelines (CNN, RNN, LSTM) for demand forecasting and customer trend analysis, boosting the accuracy of pricing models and improving revenue projections. Applied NLP frameworks (spaCy, NLTK, Hugging Face) to synthesize insights from 3M+ unstructured text reviews, uncovering recurring service issues and driving 15K+ annual positive guest ratings. Deployed and monitored ML models using AWS Lambda, S3, RDS, and MLflow, integrating real-time data feeds into production environments for automated decision-making. Optimized PostgreSQL and MongoDB schemas f