Summary
Christian Sweet is a Software Engineer (L4) at Google with a decade of engineering experience and an academic foundation from UT Austin where he’s pursuing an MS in Computational Science, Engineering, and Mathematics. He has worked across Android Automotive—focusing on surround view and scene intelligence (CV/ML)—and core data storage productivity, efficiency, and safety, bringing both systems and applied machine learning experience. Christian’s background spans internships and roles that reduced human curation in search, improved streaming data consistency, and prototyped embedded ML feasibility, showing a knack for turning research into production-ready solutions. He mentors and taught early-career researchers, led undergraduate research projects involving large-scale corpus analysis and real-time computer vision for 3D printing, and rebuilt a full-stack web presence for a campus radio station. Comfortable in Python, Java, CV/OpenCV, and distributed systems tooling, he blends academic rigor with pragmatic engineering to deliver reliable, instrumentation-driven features. Based in New York, he’s especially interested in using computer engineering to accelerate other fields, often approaching problems from both ML and systems perspectives.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at The University of Texas at Austin