Constructed clean, maintainable Python code in a Linux environment to apply deep learning algorithms to a multitude of computer vision and speech recognition related projects

Championed the idea to create web-based demos for AI projects and worked as a full-stack engineer to implement 10+ demos

Automated laborious tasks to increase working efficiency by ~70%

Managed teams of around three to eight engineers and interns

Conducted code reviews to ensure all code was bug-free, well optimized, and up to company standards

Collaborated with team members in on-site, hybrid, and full remote environments using tools such as Git for version control and review

Engineered code for neural network training and inference on computer vision tasks using TensorFlow and PyTorch

Improved models by analyzing results and fine-tuning parameters

Debugged, optimized, and modularized code from engineers to improve performance, maintainability, and clarity

Worked with and managed large datasets consisting of images, videos, and audio samples

Conducted research into state-of-the-art neural network models in order to reverse engineer their methods

Assisted teaching an Introduction to Object Oriented Programming course taught in C++

Tutored students on core concepts such as classes, functions, loops, and other object oriented programming basics

Collaborated with professors to create weekly lab assignments enforce class curriculum

Aided individual students who were struggling with class concepts or assignments