Summary
Amir Darwesh is a Senior Autonomy Engineer with nine years of experience building perception and control systems for autonomous vehicles, currently contributing to Motional’s self-driving stack. He brings deep hands-on expertise in ROS, C++, Python, Linux, LiDAR-based vehicle detection, object tracking, and data analysis, with a proven track record from internships to technical lead roles at Embark Trucks. His academic foundation—B.S. (Cum Laude) and M.S. in Mechanical Engineering from Texas A&M, the latter completed with a 4.0 GPA—underpins a methodical approach to robotics research and system integration. Amir has moved fluidly between research and production, turning graduate-level autonomy algorithms into road-ready software during his time at universities and industry R&D teams. He’s equally comfortable optimizing low-level control and scaling perception pipelines, and he often bridges gaps between algorithm prototyping and robust engineering practices. Colleagues describe him as a pragmatic problem-solver who pairs academic rigor with practical deployment experience.
8 years of coding experience
5 years of employment as a software developer
B.S. Mechanical Engineering, GPA 3.65, Cum Laude, B.S. Mechanical Engineering, GPA 3.65, Cum Laude at Texas A&M University
English