Andrew Reiter
Lincoln, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAndrew Reiter is a Principal Software Engineer with over 11 years of experience turning state-of-the-art algorithms into robust, production-grade autonomous systems. He co-founded Shield AI to protect servicemembers and civilians with AI-powered autonomy, leading edge-autonomy initiatives, state estimation, and system integration across multiple teams. He is currently a Principal Software Engineer at Boston Dynamics, driving architectural and performance optimization for the Atlas platform. His diverse leadership history includes Principal Software Architect at ThorCon US and senior roles at Shield AI and Draper Laboratory, with deep expertise in sensor fusion, SLAM, ROS, and compute-efficient embedded systems. He holds a BS in Chemical Engineering from Northwestern and an MS in Robotics from Harvard, blending rigorous engineering with hands-on software craft. In open-source work, he contributed to blakeblackshear/frigate, improving ffmpeg-based processing, Jetson/TensorRT integration, and iOS H.265 playback for real-time video workloads.
11 years of coding experience
10 years of employment as a software developer
Master of Science - MS, Robotics, Master of Science - MS, Robotics at Harvard UniversityBachelor of Science - BS, Chemical Engineering, Bachelor of Science - BS, Chemical Engineering at Northwestern University
Github Skills (13)
docker10
ffmpeg10
python10
dockers10
cicd9
tensorrt9
computer-vision9
object-detection8
camera8
ai8
home-automation7
linux7
go6
Programming languages (7)
Github contributions (5)
blakeblackshear/frigate
May 2023 - Jul 2024
NVR with realtime local object detection for IP cameras
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:27 reviews, 17 PRs, 126 comments in 1 year 2 months
Contributions summary:Andrew primarily contributed to the optimization of the Frigate NVR system. Their work involved improving the efficiency of the ffmpeg processes, specifically by reducing framerate before downscaling and implementing hardware acceleration. They also refactored the code to use ffmpeg version checking and improved the compatibility for Nvidia Jetson devices, including TensorRT integration and associated Docker build configurations. Additionally, they worked on improving the iOS playback of H.265 clips.
realtimecameramqtthome-automationobject-detection
madsciencetist/teamshield
Jun 2016 - Aug 2023
Contributions:15 pushes, 1 branch, 1 comment in 7 years 3 months
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