Architected highly-available AWS ingestion pipelines using Python and Docker, processing 280GB of telemetry data.

Developed responsive Next.js/React frontend interfaces to consume real-time APIs, improving dispatch visibility.

Utilized integrated AI models within FastAPI microservices to automate data extraction, achieving 90% accuracy.

Championed TDD methodologies and automated CI/CD deployment pipelines, ensuring zero-downtime container rollouts.

• Designed scalable PostgreSQL schemas with Row Level Security to securely index sensitive geospatial web data.

• Built an MLOps pipeline to accelerate physical therapy research for the lab’s academic users.

• Researchers spent hours on manual data processing and environment setup for each experiment.

• Automated a complex Docker workflow, integrating multiple computer vision models.

• Created a one-command system that transformed raw video into analysis-ready 3D skeletal data.

• Reduced research setup time from 4 hours to 45 minutes, boosting experiment velocity.