I ship models to production
Specialized in GenAI, and end-to-end AI/ML deployment. Turning research into reliable, scalable production systems.
What I Bring
Core competencies that define my approach to ML engineering
End-to-End ML Ownership
From data pipelines to production serving, I own the full ML lifecycle
Production-First Mindset
Every model is designed with monitoring, fallbacks, and scalability in mind
System Reliability
SLOs, alerting, and graceful degradation are non-negotiable requirements
Featured Projects
Selected work demonstrating end-to-end ML system design
AI-Driven Graphology Analysis System
Manual graphology is subjective, inconsistent, and not scalable for digital applications
Enterprise RAG Pipeline
Engineers spending 30% of time searching for answers across fragmented documentation
Automated Machine Inspection & Control System
Manual inspection and fragmented machine communication caused inconsistent quality control and low production efficiency
Technical Strengths
Technologies and practices I use to build reliable ML systems
Machine Learning
MLOps & Deployment
Software Engineering
Cloud & Infrastructure
Interested in working together?
I'm always open to discussing ML engineering roles, Career opportunities, or interesting technical challenges