Summary
Andrew Mendez is a research-focused machine learning engineer with 12 years of experience applying deep learning and computer vision to domains spanning defense, autonomous vehicles, bio-pharma, and augmented reality. He combines dual MS degrees from Cornell Tech and Technion and a Stanford AI certificate with hands-on production work building distributed training, hyperparameter tuning, and real-time mobile segmentation models. At companies from Clarifai and Determined AI (now HPE) to CACI, he’s bridged research and engineering to deliver end-to-end ML systems for high-stakes applications. His background in HCI and AR—dating back to MIT Media Lab projects—informs a pragmatic approach to human-centered model design and real-time inference. Based in Rockville, MD, he’s equally comfortable prototyping research ideas and hardening them for production-scale distributed training. A less obvious strength is his track record of reducing operational costs through infrastructure automation and efficient on-device model design.
12 years of coding experience
8 years of employment as a software developer
Masters of Science (Dual Degree with Cornell Tech) Applied Information Science, Masters of Science (Dual Degree with Cornell Tech) Applied Information Science at Technion - Israel Institute of Technology
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at University of Central Florida
Masters of Information Science Connective Media, Masters of Information Science Connective Media at Cornell Tech
Graduate Certificate Artificial Intelligence, Graduate Certificate Artificial Intelligence at Stanford University