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@rapidrobotics.com
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5 phones found area 952, 646, 607, and 877
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LinkedIn matched
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Kyle Dorman is listed as Computer Vision & Machine Learning at Augmodo, based in San Francisco, California, United States. AeroLeads shows a work email signal at rapidrobotics.com, phone signal with area code 952, 646, 607, 877, and a matched LinkedIn profile for Kyle Dorman.
Kyle Dorman previously worked as Machine Learning Engineer at Augmodo and Computer Vision Researcher at Rapid Robotics, Inc. Kyle Dorman holds Biological And Environmental Engineering from Cornell University.
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AeroLeads found 3 current-domain work email signals for Kyle Dorman. Compare company email patterns before reaching out.
10+ years of experience in computer vision, machine learning and fullstack engineering. As the first engineering hire for a YC backed startup, I helped grow the company to unicorn status. I specialize in zero to one prototypes as well as leading teams scaling MVPs to mature, robust systems. I have experience in the retail, robotics, and e-commerce industries. I love to solve real production challenges and find efficient and creative solutions to customer problems. I am particularly motivated by solutions that positively impact the world.
Listed skills include Renewable Energy, Sustainability, Ruby On Rails, Javascript, and 2 others.
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- Outlined company’s year one ML roadmap. Detailed types of ML models necessary and existing relevant research papers, datasets, and open source projects to leverage- Built a cloud based machine learning inference pipeline to detect, track, and classify products and empty shelf areas of retail stores collected from human mounted cameras- Trained bounding.
San Francisco, CA, US
- Refactored an existing PyTorch keypoint estimation model used to predict single object 6D poses (position and orientation). Resulted in significant improvements to the model's speed and accuracy- Improved robustness of keypoint estimation model trained only on synthetic data by adding image augmentations which helped close the gap between synthetic and.
San Francisco, California, US
Human Keypoint Detection- Architected a flexible human keypoint estimation deep learning training code base with Tensorflow which enabled team members to easily iterate on model architectures and model outputs- Retrained OpenPose model with mixed precision for 2x inference speed with no loss in accuracy- Designed a new pose model based on latest research.
Boston, Massachusetts, US
- Spent time on frontend team, iOS mobile team, and backend team- Overhauled legacy Objective-C iOS app by porting pieces of the app to Swift as a member of a four-person team- Migrated legacy desktop web apps to responsive web apps on a team of three- Administered Software Engineering Summer Apprentice Program. Led recruiting, interviewing and project.
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Kyle Dorman works for Augmodo.
Kyle Dorman is listed as Computer Vision & Machine Learning at Augmodo.
AeroLeads has found 3 work email signals at @rapidrobotics.com for Kyle Dorman at Augmodo.
AeroLeads has found 5 phone signal(s) with area code 952, 646, 607, 877 for Kyle Dorman at Augmodo.
Kyle Dorman is based in San Francisco, California, United States while working with Augmodo.
Kyle Dorman has worked for Augmodo, Rapid Robotics, Inc, Standard Cognition, Gilt.Com, and Enernoc.
You can use AeroLeads to view verified contact signals for Kyle Dorman at Augmodo, including work email, phone, and LinkedIn data when available.
Kyle Dorman holds Biological And Environmental Engineering from Cornell University.
Kyle Dorman is listed with skills including Renewable Energy, Sustainability, Ruby On Rails, Javascript, Node.Js, and Sql.
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