Avina Avina

I’m a Software Engineer specializing in high-performance AI systems and compilers, currently at QuantAI where I build the infrastructure that makes low-latency trading possible at machine speed. My work lives at the intersection of compiler engineering and quantitative finance. I architected ALX, a domain-specific language compiler with a full MLIR/LLVM backend that emits optimized SIMD machine code, outperforming NumPy by 5X on financial compute workloads and earning a patent from NYU. From designing Python-to-MLIR FFI bridges that preserve researcher ergonomics while hitting compiled-C performance, to slashing portfolio backtesting runtimes from 24 hours to 30 minutes, I obsess over the gap between theoretical performance and what actually runs fast in production.

I hold a Master’s in Computer Science from New York University, Bachelor’s in Computer Science and Engineering from Vellore Institute of Technology and bring experience across the full stack; backend systems at scale, deep learning, cloud infrastructure, and the kind of low-level optimization work that most engineers never touch.

My 2 years as a Backend Software Engineer at PharmEasy, a unicorn startup, taught me how to build and manage large-scale systems. Previously as a Research Intern at QuantAI I was pushing the boundaries of high-frequency trading technology. I achieved a 500X speed improvement in trading algorithms through low-level CPU optimizations and assembly-level programming. I also worked on the LLVM compiler for the domain-specific language. This work earned recognition through our successful NSF federal grant pitch and a patent from NYU for our new domain-specific language.

My Research Internship at Indian Space Research Organization was a turning point, where my work on the Normalization of satellite images using Machine Learning with Image Processing sparked my deep interest in AI. I’ve continued exploring this passion through projects in areas like Machine Learning, Deep Learning, and Natural Language Processing, even participating in the recent Amazon GenAI hackathon in New York.

Beyond AI, I have experience in web development, mobile app development, and big data systems through projects and internships. At Develop for Good, I worked as Software Engineer Intern to Engineering Manager Intern, where I led a team of 9 engineers while building an AI-based mobile application, developing both technical and leadership skills. I have also interned at Amilcar Technologies where I gained web development skills. The details can be found in CV. I really enjoyed learning and implementing these skills to solve interesting problems. The details can be found in Projects.

I’m excited about emerging technologies and eager to apply my skills in building innovative, high-performance systems that solve complex real-world problems.