Developed an AI-powered platform designed to automate and enhance audio mixing and mastering workflows, enabling high-quality audio production without the need for traditional manual engineering.

Built backend systems to process and analyze audio inputs, applying intelligent algorithms to optimize sound balance, clarity, and overall quality. Designed automated pipelines that handle tasks such as level balancing, equalization, compression, and mastering, delivering consistent and production-ready outputs.

Focused on creating a scalable and efficient architecture to support real-time or batch audio processing, ensuring reliability and performance across various audio use cases. Collaborated on integrating AI-driven models to replicate and improve standard audio engineering practices.

Contributed to the development of a large-scale job data platform, focusing on web scraping, automation, and backend data systems to power job aggregation and analytics.

Designed and maintained automated scraping pipelines to collect job listings from multiple sources, ensuring consistent data flow and high coverage. Built systems for data cleaning, normalization, and deduplication, improving the accuracy and usability of job data across the platform.

Developed backend processes to handle high-volume data ingestion and updates, enabling near real-time synchronization of job postings. Implemented automation workflows for monitoring scraper performance, handling failures, and maintaining data freshness.

Collaborated with cross-functional teams to support downstream systems, including search, filtering, and data-driven features, by delivering structured and reliable datasets.

Developed and scaled the backend infrastructure for an AI-powered job platform, focusing on data acquisition, processing, and system reliability.

Led the design and implementation of high-performance web scraping pipelines, aggregating millions of job listings from multiple global sources. Built robust systems for data normalization, deduplication, and enrichment, ensuring high-quality and structured job data.

Architected and maintained scalable backend services using Python (FastAPI), handling real-time data ingestion and API delivery. Designed efficient database schemas and querying strategies (MongoDB/PostgreSQL) to support large-scale job datasets and fast search operations.

Implemented automation workflows to continuously monitor, update, and validate job postings, improving data freshness and platform accuracy. Collaborated closely with frontend and AI teams to enable intelligent job matching and recommendation features.