Kyle Dorman
Machine Learning Engineer at Augmodo
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolKyle Dorman is a Machine Learning Engineer with 12 years of experience building production computer vision systems across retail, robotics, and e-commerce. As the first engineering hire at a YC-backed startup, he helped scale the company to unicorn status and repeatedly takes products from zero-to-one—prototyping models and leading teams to mature, robust deployments. He has deep hands-on expertise in pose estimation, multi-view 6D pose and reprojection refinement, real-time multi-camera tracking, and retail shelf detection, often combining open-source research (GroundingDINO, Segment Anything) with custom tooling for auto-labeling and deployment. Kyle excels at closing the sim-to-real gap through synthetic-data workflows and clever augmentation, and has driven measurable production gains (e.g., 2x inference speed, 50% fewer identity swaps, sub-millimeter pose accuracy). Based in San Francisco, he is motivated by efficient, creative solutions that deliver real-world impact and enjoys tackling the messy engineering problems that take prototypes into reliable systems.
12 years of coding experience
9 years of employment as a software developer
Biological and Environmental Engineering, Biological and Environmental Engineering at Cornell University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (107)
python10
classifier10
deep-learning10
bayesian-deep-learning10
neural-network10
data-science10
tensorflow10
pytorch10
machine-learning10
object-tracking9
ml9
jax9
re-identification9
deep-neural-networks9
multi-object-tracking9
Programming languages (8)
Github contributions (5)
Rui-Santos/cbtc
Nov 2013 - Jan 2014
Contributions:32 commits in 2 months
kyle-dorman/steering-angle-predictor
Mar 2017 - Sep 2017
Contributions:47 commits, 43 pushes, 1 branch in 6 months
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