Senior Software & ML Engineer crafting scalable systems, AI agents, and resilient infrastructure. Where research meets real-world impact.
Building robust, scalable systems. Backend services, distributed architectures, and clean code that doesn't make future-me cry.
From notebooks to production pipelines. Training models, optimizing inference, and making sure they actually work at scale.
Exploring new ideas, running experiments, and occasionally stumbling onto something that works. Some become papers, some become products.
CI/CD, monitoring, deployment pipelines. Because "it works on my machine" isn't a deployment strategy.
LLMs, transformers, computer vision, reinforcement learning. Currently exploring efficient fine-tuning and model optimization techniques.
Consensus algorithms, fault tolerance, and the art of making things work when servers inevitably fail.
Bridging the gap between papers and production. Reading arxiv, implementing ideas, and figuring out what actually works in practice.
Working on something interesting? Need help with system design, ML infrastructure, or research implementation? Always happy to chat about ideas, code, or the latest papers.