# Alice Leung > Senior Machine Learning Engineer at LinkedIn Location: San Francisco Bay Area, United States Profile: https://flows.cv/aliceleung As a Machine Learning Engineer at LinkedIn, I apply my expertise in natural language understanding and statistics to develop and optimize algorithms and models that enhance the relevance and user experience of the platform. With over five years of experience in various domains of machine learning, data science, and actuarial science, I have honed my skills in Python, SQL, and data science, and gained valuable insights into different industries and applications of AI. I have also contributed to the academic and professional communities through teaching, and research. My mission is to use my passion and knowledge of AI to solve real-world problems and create positive impact. I value collaboration, innovation, and diversity, and I am eager to learn from and share with others in the field. ## Work Experience ### Test AI Engineer @ GSOBA Jan 2025 – Present This is for internal testing purposes ### Sr. Software Engineer, Machine Learning @ LinkedIn Jan 2024 – Present | Sunnyvale, California, United States ### Machine Learning and Relevance Engineer @ LinkedIn Jan 2022 – Jan 2024 | Sunnyvale, California, United States ● Led a team of 3 to successfully launch LinkedIn's new generative AI job coach feature for members to use natural language queries in job search, for example "Find me software engineering jobs in the bay area". Closely collaborated with XFN partners such as Product and Backend Eng to influence the roadmap and resolve blockers. ● Designed and implemented a unified embedding of member's skills from various sources (explicit, resume, linkedin learning, etc) to consolidate and improve skills representation in downstream models. Improved job recommendation metrics and filed patent for this novel idea. ● Unified 2 LTS AI models recruiter search and recommended matches to reduce maintenance cost and training time by 30%, improving developer productivity and experimental velocity. ### Machine Learning Intern @ LinkedIn Jan 2021 – Jan 2021 Intern on AI foundation team ● Improved salary range predictions on job postings by implementing Monte Carlo Dropout and Deep Ensembles techniques to calculate model uncertainty. ● Implemented and tested the new model end-to-end, including the offline changes to train the model in Tensorflow and deployed to production, resulting in increase in job views with inferred salary. ### Teaching Assistant @ University of Waterloo Jan 2020 – Jan 2021 ### Siri Natural Language Understanding Intern @ Apple Jan 2019 – Jan 2019 | Cupertino, California, United States ● Researched and ran experiments to develop a new agile model and feature creation pipeline to reduce experiment time from several hours to minutes ● Built a front end prototype and implemented a custom component in the pipeline to feed a new feature vector into the model ### Research Assistant @ University of Waterloo Jan 2019 – Jan 2019 • Used natural language processing in computational rhetoric projects • Researched rhetorical figures and neurocognitive affinities • Designed and researched ideas to support game development ### Machine Learning Intern @ Trifacta Jan 2019 – Jan 2019 | San Francisco, California, United States • Analyzed product usage data using statistical tests to segment customers and identified activities that drive revenue using data visualizations • Implemented fully automated executive reports by writing flows in Trifacta to analyze the data and output quarterly results to Data Studio • Applied feature engineering to 500,000 data points and over 100 features to reduce the dataset and improve prediction accuracy by 20% • Trained a random forest and a SVC model to predict customer life cycle ### Advanced Analytics Co-op @ Economical Insurance Jan 2018 – Jan 2018 | Waterloo, Ontario, Canada • Implemented a random forest with an AUC of 0.96 to automate auto claim fraud detection and improve the claim team’s efficiency • Automated and increased precision in fraudulent claim tagging by using SQL • Built interactive dashboards to display metrics to quantify the impact of the quarterly frequency, and severity due to attritional weather on the loss ratio ### Actuarial Co-op @ Economical Insurance Jan 2017 – Jan 2017 | Toronto, Ontario, Canada • Updated pricing models for renewal premiums and tested assumptions • Tuned a GLM by rigorously testing the AIC and fitting additional variables for microrating for risk assessment ### Actuarial Co-op in Financial Risk @ Manulife Jan 2017 – Jan 2017 | Toronto, Ontario, Canada • Used Bloomberg to collect data sets for scenario generation and updating model parameters • Developed market shocks for stress testing by examining historical movements of global markets ### Research Assistant @ University of Waterloo Jan 2016 – Jan 2016 ### Swim Instructor and Lifeguard @ Olympian Swimming Jan 2013 – Jan 2015 ## Education ### Master of Mathematics in Statistics University of Waterloo ### Bachelor of Mathematics in Computer Science and Statistics University of Waterloo ### OSSD and International Baccalaureate Diploma Victoria Park CI ## Contact & Social - LinkedIn: https://linkedin.com/in/alicehyleung --- Source: https://flows.cv/aliceleung JSON Resume: https://flows.cv/aliceleung/resume.json Last updated: 2026-04-01