About Me

AI/Software Engineer focused on production ML systems and enterprise architecture

Who I Am

I'm a software and machine learning engineer working primarily on production systems — the kind that need to be shipped, maintained, and iterated on inside real products.

My background combines applied AI with strong systems engineering — from building ML-powered features in regulated SaaS environments to low-level game development with C++ and OpenGL.

What I Work On

Most of my experience is around applied ML in larger software environments: backend services, data pipelines, evaluation workflows, and the glue that holds them together. I'm comfortable moving across layers when needed, especially when things break.

Current focus areas:

  • Production ML Systems: Building and refining end-to-end ML pipelines
  • Automation & Tooling: Evaluation workflows and maintainability tooling
  • Agentic Workflows: Experimenting with RAG and autonomous systems

How I Approach Problems

  • Clear System Boundaries: I believe in well-defined interfaces and predictable behavior
  • Debuggability First: I prefer solutions that are easy to understand over clever shortcuts
  • Operational Impact: I think about deployment, monitoring, and maintenance from day one
  • Incremental Iteration: Working software over perfect design

Experience

  1. Machine Learning Engineer Dec 2024 – Present
    Core Solutions Inc.
    • Built and owned end-to-end ML-powered product modules within a modern SaaS EHR platform
    • Designed modular Python-based ML services exposed via REST APIs
    • Translated business requirements into deployable AI functionality
    • Led Enterprise Data migration from heterogeneous environments
  2. Game Developer May 2024 – Nov 2024
    Game Design Plus
    • Developed event-driven, real-time gameplay systems with strict performance constraints
    • Designed UI/state transitions and debugged complex interactive systems

Education

Bachelor of Technology in Computer Science — GPA: 9.21/10

Achievements

  • National level academic competition experience demonstrating strong analytical ability
  • Hackathon experience delivering end-to-end ML and NLP applications under tight constraints