I have worked in high-pressure product environments, owning backend architecture, search and retrieval infrastructure, deployment pipelines, and performance optimization. My work has supported enterprise customers including Microsoft, Amazon, Uber, PayPal, Target, and Go-JEK.
Alongside industry experience, I am a PhD student in Machine Learning, working on modern ML models and retrieval systems. I focus on pragmatic, engineering-first applications of ML rather than purely theoretical work.
I typically help clients with:
Debugging slow or unstable Python / Django systems
Designing and fixing Elasticsearch-based search and ranking pipelines
Refactoring legacy codebases and managing dependency upgrades
Diagnosing production performance issues (CPU, memory, query latency)
Integrating machine learning models into backend services