I am a software engineer with a focus on distributed systems and applied machine learning. I've built scalable ML infrastructure, optimized high-performance compute frameworks, and designed robust, production-grade APIs at companies like Palantir, Intel, Google, Scale AI.

Across these roles, I've engineered fault-tolerant backend architectures, accelerated cloud and distributed workflows, and integrated advanced ML models into real-world systems. I thrive in lean, fast-moving teams and enjoy building systems that balance performance, scalability, and clarity.

I hold a B.S. in Computer Science from Johns Hopkins University, where I concentrated in Software Engineering and Natural Language Processing. My work sits at the intersection of intelligent systems and large-scale software design—driven by a builder's mindset and a deep focus on engineering systems that scale with impact.