# Ayush Baid > Skydio | Amazon | Goldman Sachs Location: San Francisco Bay Area, United States Profile: https://flows.cv/ayushbaid ## Work Experience ### Senior Autonomy Engineer @ Skydio Jan 2025 – Present | San Francisco Bay Area Working on autonomous missions stack (drone + cloud) and 3D Scan as part of the Inspection and Mapping team ### Autonomy Engineer @ Skydio Jan 2023 – Jan 2025 | San Francisco Bay Area Worked on the 3D scan software: porting it to the new vehicle platforms and developing new features ### Computer Science Fellow @ Open Avenues Foundation Jan 2024 – Present | San Francisco Bay Area ### Software Developer @ Amazon Jan 2021 – Jan 2023 | Seattle, Washington, United States I work in the Alexa Multitasking team as a software engineer. Our team owns a service which owns and manages skill sessions, powering various multitasking capabilities on Alexa. My major contribution till date has been in the Skill Resumption program: https://developer.amazon.com/en-US/blogs/alexa/alexa-skills-kit/2020/07/make-it-easier-for-customers-to-pick-up-where-they-left-off-with-skill-resumption. I have been working on handling the onboarding and debug requests for skill developers as part of our private beta program. I am also working on preparing the feature for a public launch: designing services, writing code, testing infrastructure, and dev-ops. ### Contributor @ GTSFM Jan 2020 – Jan 2021 | Atlanta, Georgia, United States I am a contributor to the Georgia Tech Structure From Motion (GTSFM) [https://github.com/borglab/gtsfm/]. GTSFM is a global structure-from-motion pipeline, which runs can run clusters. We leverage NVIDIA's Dask framework to enable each component of the SLAM pipeline (like feature detection, matching, averaging, bundle adjustment) etc to run on clusters. I have created the base API of many different modules for GTSFM to create a plug-and-play software where researchers and developers can develop facades for their algorithm and utilize all remaining components of GTSFM to run 3D reconstruction. I have also ported many different front-end algorithms for feature detection and matching. This includes both deep networks like SuperPoint and SuperGlue, and classical methods like SIFT and Ransac. Utilizing the distributed computing offered by GTSFM, I was able to benchmark 15000+ combinations of front-end (by using different algorithms, networks, and hyperparameters). ### Graduate Teaching Assistant @ Georgia Institute of Technology Jan 2019 – Jan 2021 | Greater Atlanta Area I was a Teaching assistant for the computer vision course for 4 semesters. As a TA, I was involved in creating new assignments from scratch (in areas like stereo vision, object detection, deep learning, etc). I also graded exams and assignments, conducted office hours, and presented the developments in deep-learning for SLAM to the class ### Software Engineer Intern @ Amazon Jan 2020 – Jan 2020 | Seattle, Washington, United States I was an intern at the Alexa multitasking team. I built a visualization tool to reconstruct the lifecycle of a skill, and the interactions between different skill sessions in multitasking scenarios (where more than one skill can coexist in our service) ### Analyst (Software Development) @ Goldman Sachs Jan 2017 – Jan 2019 | Bengaluru Area, India I worked in the cloud team for the Risk division, handling the risk metric calculation workflow and its distribution on the cloud farm. Summary: • Designed a new distributed computing system based on microservice architecture using Kafka and MongoDB to calculate risk for FRTB regulation, generating global data stores and reduced debug time by ~20% for teams • Built the task packaging and runtime prediction model for the in-house distributed computing system; contributed to reduction of ~10% in compute costs • Developed a new data engineering system to capture the runtime metadata of millions of pricing sessions ### Signal Processing Intern @ Carnot Technologies Private Limited Jan 2017 – Jan 2017 | Mumbai Area, India • Designed an algorithm to derive the engine r.p.m using data from a proprietary sensing technology; Used digital filters to clean the input data and modeled the shift in r.p.m as a Gaussian distribution to obtain robust and stable r.p.m estimates ### Open Source Developer @ FOSSEE IIT Bombay Jan 2015 – Jan 2017 | Mumbai • Developed and tested signal processing functions in domains like pseudospectrum evaluation and filter design ### Software Engineering Intern @ Sony Jan 2015 – Jan 2015 | Tokyo, Japan • Developed a cloud-based testing platform for Android applications with on-demand device allocation service • Injected stubs in the Android source code to work-around network restrictions in Android’s native emulators ### Junior Design Engineer @ IIT Bombay Racing Jan 2013 – Jan 2014 | Mumbai • Worked in the battery and battery management system for our college's race care entry to the Formula Student UK competition ### Core Developer @ Exzalt Jan 2013 – Jan 2014 Handled Android app development and backend for apps. ## Education ### Master of Science - MS in Computer Science Georgia Institute of Technology ### Bachelor of Technology in Masters of Technology, Electrical Engineering Indian Institute of Technology, Bombay ### Metas of SD ## Contact & Social - LinkedIn: https://linkedin.com/in/ayushrb --- Source: https://flows.cv/ayushbaid JSON Resume: https://flows.cv/ayushbaid/resume.json Last updated: 2026-04-01