Martin Ethier
Engineering at Applied Intuition
Waterloo, Ontario, United States
Summary
👤
Senior🎓
Top SchoolMartin Ethier is an ML engineer and MASc candidate at the University of Waterloo with nine years of hands-on experience building perception and simulation systems for autonomous vehicles and robotics. He has shipped simulation-driven training pipelines and domain-randomization tools (Unity/C#) to generate data for object detection and ground segmentation, and has trained production-grade models such as YOLOv7 for forklift detection. His research blends sim-to-real lane detection and LiDAR/3D perception, resulting in a co-authored IV2022 paper and applied tools for semantic labeling and visualization. Comfortable across PyTorch, TensorFlow, ROS, and MLOps stacks, he also led R&D for continuous training pipelines at DarwinAI and prototyped industrial imaging and spectral ML solutions. Colocated in Waterloo, he pairs academic research with practical deployment experience—often turning simulators and visualization tooling into datasets and models that match real-world performance.
8 years of coding experience
2 years of employment as a software developer
Master of Applied Science (MASc), Electrical and Computer Engineering, Master of Applied Science (MASc), Electrical and Computer Engineering at University of Waterloo
English, French
Github Skills (41)
3d-reconstruction10
computer-vision9
photogrammetry9
3d-graphics9
pytorch9
tensorboard9
monte-carlo-tree-search9
geometry8
gomoku8
deep-reinforcement-learning8
structure-from-motion8
deep-learning8
3d8
machine-learning8
jupyterlab8
Programming languages (4)
Github contributions (5)
MartinEthier/config_files
Feb 2020 - Jul 2022
Contributions:4 pushes, 1 branch in 2 years 4 months
MartinEthier/end-to-end-driving
Apr 2020 - Aug 2022
Contributions:56 pushes, 1 branch in 2 years 4 months
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