# Amy Zhao > SWE @ Salesforce | Econ + CS @ Yale Location: San Francisco, California, United States Profile: https://flows.cv/amyzhao ## Work Experience ### Software Engineer @ Salesforce Jan 2024 – Present | San Francisco, California, United States Team: Data Streaming Connectors (Data Cloud) ### Research Assistant @ Yale Department of Economics Jan 2024 – Present ### Teaching Assistant @ Yale University Jan 2021 – Jan 2024 | New Haven, Connecticut, United States – Past Course Assignments: CPSC 201 (Intro CS | Fall '21), CPSC 202 (Discrete Math | Spring '22, Fall '22, Fall '23), CPSC 365 (Algorithms | Spring '23, Spring '24, Summer '24) – Collaborated with multiple teams of undergraduates and faculty to provide office hours, feedback, homework grading, one-on-one code debugging, discussion sections, review sessions, and exam support. – Piloted a hybrid (in-person and online) office hours program to increase flexibility and availability of help and ensured at least four hours of support daily. – Worked with more than 900 students within the computer science department through seven semesters of introductory computer science, discrete math, and algorithms. – Promoted to lead ULA after two semesters, nominated most valuable teaching assistant from student and professor votes, and awarded one of two top department prizes. ### Software Engineer Intern @ Salesforce Jan 2023 – Jan 2023 | San Francisco, California, United States – Implemented an API to facilitate the communication of vital data stream metadata across services in the Data Cloud. – Customized and deployed Amazon Web Services (AWS) infrastructure through Terraform to automate daily triggers for a set of alerts meant for monitoring. – Created metrics, logs, and alerts for failed data streams to drastically reduce the manual workflow for on-call engineers responsible for restarting failed streams and the overall cost to serve in the Data Cloud. – Designed a data stream health indicator measuring unprocessed AWS S3 data files to prevent data loss in storage solutions with limited retention rates based on the file modification date and the metadata generated as data passes through bronze and silver layers of the medallion-based architecture. ### Software Engineer Intern @ Salesforce Jan 2022 – Jan 2022 | San Francisco, California, United States – Worked on the Flow Builder Interface in the Salesforce Core Product to bring a reactive feature, which enables users multiple view options during process automation, from conception to the pre-production stage. – Shipped changes to production for the Flow Builder Interface which enabled better use of screen real estate. – Developed a custom, reusable component using the Lightning Web Components UI framework that provides interoperability with existing app components. – Led discussions and made vital decisions for key elements of the features in development, collaborating with the UX and accessibility teams to enable functional and sustainable development. ### Software Engineer Intern @ The Johns Hopkins University Applied Physics Laboratory Jan 2019 – Jan 2019 | Laurel, Maryland, United States – Developed a machine learning algorithm to classify human and bot language based on grammatical differences in syntax. – Scraped tweets through Twitter’s API, labeled the posts as human or bot by cross-referencing other bot detection tools, and used the data to train the algorithm. – Studied and applied eigenvector centrality measures to identify important players and their influence on public opinion within Twitter’s social network. ### Software Engineer Intern @ The Johns Hopkins University Applied Physics Laboratory Jan 2018 – Jan 2019 | Laurel, Maryland, United States – Developed a Python algorithm which parsed, stored, and visualized CSI extracted from a WiFi router in real time in order to highlight physical motion in the presence of the router. – Trained decision tree, support vector machine, k-nearest neighbors, and random forest machine learning algorithms to classify CSI as different types of motion, achieving a 95% average accuracy rate for the random forest algorithm. – Published a peer-reviewed research paper for IEEE titled “WiFi Motion Detection: A Study into Efficacy and Classification”. ## Education ### Bachelor of Science - BS in Computer Science + Economics Yale University ### River Hill High School ## Contact & Social - LinkedIn: https://linkedin.com/in/amyxzhao --- Source: https://flows.cv/amyzhao JSON Resume: https://flows.cv/amyzhao/resume.json Last updated: 2026-04-10