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About

I’m a security researcher turned Tech Recruiter with a focus on Machine Learning Research. My unconventional path began at 15 with game modifications and evolved through system administration into serious security work. I’ve participated in bug bounty programs with major tech companies including Google, Apple, Meta, Microsoft, Amazon, and Uber. This deep technical foundation allows me to evaluate engineering talent in ways most recruiters simply can’t.

My path to Tech Recruitment wasn’t conventional:

GitHub Contribution Graph showing consistent daily coding activity

My GitHub contribution graph reflects my continued commitment to code development despite my career transition.

Current Work

Today I operate in two distinct spheres: technical recruiting and machine learning research. In recruiting, I specialize in identifying exceptional engineering talent for unique, high-stakes roles. My research focuses on sequence modeling for large-scale foundation models and the practical challenges of deploying ML systems in real-world environments.

I’m particularly interested in how foundation models will reshape computing interfaces over the coming decades, especially for complex, exploratory domains. I’m also building Glide, an AI-powered job matching platform that bridges my recruiting expertise with cutting-edge ML research.

Philosophy

I believe innovation emerges at the intersection of diverse disciplines. My journey from security research through recruiting to ML research demonstrates how unexpected paths often lead to the most interesting work.

”Things just happen to happen. They don’t happen because they’re supposed to.”

Benjamin Hoff, The Tao of Pooh

This philosophy resonates with me as I view my experiences as interconnected elements contributing to a comprehensive understanding of complex systems. I value adaptability and collaboration, combining diverse perspectives to create innovative solutions.

My professional philosophy centers on possibility—viewing challenges as opportunities for growth.