San Francisco Bay Area
"Studying less and less about more and more until I know nothing about everything." Hey! My name is Ricardo Miranda and I have an avid background and vested interest in all sorts of fields, ranging from physics, mathematics, computer science to political science, biomechanics, and the humanities. For the past two years, I worked with Google through Astreya to support three different programs: Chrome, Pixel, and Wear. In each program, I strived to make day to day operations easier and more robust by learning different technologies (Google Sheets, AppScripts, Python, Shell, etc.) required to better perform my tasks. With my improvements and optimizations, I not only perform better but I try my best to share best practices with other teams so that they are able to better perform in their day to day tasks as well. I have a B.S in Computer Science with a concentration in Mathematics and Physics and share a passion for programming, scripting, and managing technical operations and I especially love to automate wherever I can! For me, growing isn't an option, it is a necessity. ----- As an additional note, I am currently on the market looking for positions that focus on automation and scripting. I want to make a pivot to systems/software engineering. Please do not reach out to me for about technician roles.
Debugged and repaired assembly units by testing various components under 10 separate unit testers. Provided support to production line whenever unit testers experienced failures by thoroughly documenting SOPs regarding debugging procedures. Created and maintained dozens of troubleshooting guides to reference whenever a failure occurs at a specific unit tester; includes documenting new failure/error codes and analyzing root causes of error. Automated daily activities, such as failure analysis of unit failures and reporting of bugs to customer via Google Sheets and Apps Scripts.
Optimized logistics and operations of the WearOS distribution program by implementing scripts to increase faster flashing of WearOS devices, increasing throughput by upwards of 400% on a weekly basis. Programmed various Google Apps Scripts to use with Google’s internal ticketing tool to manage tickets across various programs, including but not limited to WearOS, resulting in faster ticket closure rates. Created various tools, spreadsheets, and documentation to streamline the shipping process, allowing for a robust process to ship out devices, reducing the time required to ship dozens of packages by more than 80%.
Designed and built a work station to optimize flashing of devices during heavier weeks of traffic in order to meet deadlines. Developed an internal tracking tool to update our team on the statuses of recently shipped packages using Python and Google Apps Script. Allows users to see the statuses of 100s of packages at any point in time. Scripted multiple shell files to allow for faster flashing and logging of pixel devices using the adb and fastboot programming tools. Developed and structured 3 tools via Google Sheets and Google Apps Script for various teams within the Google Pixel warehouse regarding inventory management, physical inventory, and processing of inbound shipments for easier distribution of devices to clients.
Developed multiple Linux scripts that installed packages, upgraded to latest firmware, and prepared Linux devices to be used in the operation’s close case debugging (CCD) process immediately after receiving them, which reduced processing time by 15%. Prepared Chrome devices for CCD and development purposes via Linux terminal and worked with the chroot environment to extract hardware information, unlock devices, and enable development and boot via USB. Worked on beta development testing for the hardware id extractor tool used in the CCD process with the goal to create an all-encompassing tool that will reduce processing time by at least 50%. Fulfilled replacement requests to various Google chromebook engineering teams by providing the devices needed as well as the specific configurations that were requested. Automated process to identify cycle count discrepancies via Google Sheets and Google’s HaRT database which helped account for all 50,000 devices in the Google ChromeOS warehouse and improved cycle count accuracy.