# Richard Mao > Software Engineer l Machine Learning @ Meta Location: San Francisco, California, United States Profile: https://flows.cv/richardmao Software developer with specific interest and experience in machine learning engineering and deep learning applications in computer vision and NLP ## Work Experience ### Software Engineer @ Meta Jan 2022 – Present ASA - LLM model development App Ads Core ML - developing ML Ranking Models AI Infra ### Machine Learning Engineer Intern @ Qualcomm Jan 2021 – Jan 2021 - Automated and deployed an ML pipeline for the ESG Data Analytics thermal team using python and Jenkins for Linear Regression and RNN models that achieved under 0.5 degrees celsius root mean squared error. - Developed a novel solution for determining when models should be activated and deactivated to save CPU cycles through multivariable optimization. - Performed feature engineering and trained Random Forests, Gradient Boosted Trees, and Neural Networks to classify whether cellular devices were using 5G with 0.75 F1 score on highly imbalanced datasets. ### Project Leader @ Machine Learning at Berkeley Jan 2021 – Jan 2021 | Berkeley, California, United States - Project Leader for Industry Consulting Project with FakeNetAI on deepfake audio detection. - Devised new ResNet-LSTM models to classify audio segments from multiple datasets with an average of 0.9 F1 score for FakeNetAI’s audio deepfake detector. - Deployed model on to a web server with AWS and streamlit backend. ### Member @ Machine Learning at Berkeley Jan 2020 – Jan 2021 | Berkeley, California, United States - Built a pipeline that analyzes the content and semantics of sales calls in real time to automate CoPilot's cue card system for sales representatives. - Created custom unsupervised PyTorch word models with importance weighting and embeddings to achieve an F1 score of .75 trained on unlabeled data. ### Undergraduate Research Assistant @ Berkeley Artificial Intelligence Research Jan 2020 – Jan 2021 - Analyzed representational similarity divergence of various vision models in hierarchical pretraining strategies under Prof. Kurt Kuetzer. - Published Self-Supervised Pretraining Improves Self-Supervised Pretraining to the WACV 2022 conference. ### Computer Vision Scientist Intern @ percipient.ai Jan 2020 – Jan 2020 | Santa Clara, California, United States - Designed and trained models that reduced a vehicle labeling into an energy minimization problem solvable with graph cuts and alpha-expansion. - Incorporatied geospatial context using markov random fields and belief propagation. ### Undergraduate Research Assistant @ Berkeley RISE Lab Jan 2019 – Jan 2020 Trained traffic light object detectors with Faster R-CNN and SSD models along with an SVM to classify and output the bounding box of traffic lights in the CARLA autonomous driving challenge using Tensorflow’s Object Detection API under Prof. Joseph Gonzalez ### Intern @ San Diego Super Computer Ctr Jan 2018 – Jan 2018 | Greater San Diego Area Developed a batch scheduling efficiency analyzer that calculates efficiency and demand for nodes of SDSC's newest supercomputer, Comet, at different times of day using Python and Regex. ### Software Intern @ SEAP - SPAWAR Systems Center Pacific Jan 2017 – Jan 2017 | Greater San Diego Area - Created a low budget, single-camera autonomous vehicle with python that could navigate 4x4 street blocks. - Implemented features including lane detection, alen-alignment, street sign detection, and depth perception, etc. ### Software Developer @ Project Concern International Jan 2017 – Jan 2017 | Greater San Diego Area • Developed an iOS application that raises awareness for children in areas without sufficient access to clean water. Includes a game and links to sign up for the annual event. ### Software Intern @ TrellisWare Technologies Jan 2016 – Jan 2016 | Greater San Diego Area - Developed applications that created samples, transmitted data, and received data via radio frequency in the High Frequency band. ## Education ### Bachelor of Science - BS in Computer Science UC Berkeley Electrical Engineering & Computer Sciences (EECS) ### Westview High School ## Contact & Social - LinkedIn: https://linkedin.com/in/richard-mao --- Source: https://flows.cv/richardmao JSON Resume: https://flows.cv/richardmao/resume.json Last updated: 2026-03-29