Xiang Liu
Xiang Liu

Machine Learning Engineer

Amazon

I am at the forefront of architecting and developing Large Language Models, including Amazon Rufus, our pioneering conversational shopping assistant. My work leverages billions of data points alongside the latest in cloud technology to create personalized shopping experiences that redefine consumer interactions, marking a significant stride in data-driven commerce at Amazon’s unparalleled scale.

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Experience

  1. Machine Learning Engineer

    Amazon Search Science and AI

    Projects include

    • Amazon Rufus
    • Large-scale LLM-based data processing system
    • Personalized Shopping Experience

  2. Software Development Engineer II

    Amazon Web Services

    Projects include

    • Data Anti-Entropy Service between DynamoDB and Elasticsearch
    • DynamoDB backfill and verification system

Education

  1. M.Sc. in Computer Science (Machine Learning)

    Georgia Institute of Technology

    GPA: 4.0/4.0

    Description

    • Participated in the Online Master of Science in Computer Science (OMSCS) program while working full-time.
    • Committed 10-15 hours per week during weekends and spare time for three years to continue developing expertise in machine learning and software development.

    Coursework

    • Machine Learning: Deep Learning, Machine Learning, Robotics AI Techniques, Machine Learning for Training, AI Ethics and Society.
    • General Computer Science: Algorithms, Computer Networks, Video Game Design, Data Analytics and Security.

  2. M.Sc. in Experiment Medicine (Applied Machine Learning)

    The University of British Columbia

    Grade: 89%

    Research Area

    • Clinical data mining: predicting the depression treatment outcome using machine learning.
    • Neuroimage and Brain Connectivity analysis: analyzing the human brain network functional connectivity under different activities.

    Coursework

    • Machine Learning and Statistical Modelling: Multimodal Learning with Vision, Language and Sound, Statistical Methods for High Dimensional Biology.
    • Experimental Medicine: Molecular and Cellular Biology of Experimental Medicine, Experimental Medicine Methodology.
    Read Thesis

  3. B.Sc. in Computer Science and Statistics

    The University of British Columbia

    Grade: Major GPA 80%

    Coursework

    • Machine Learning: Artificial Intelligence, Machine Learning and Data Mining, Computational Optimization, Intelligent Systems.
    • General Computer Science: Software Engineering, Computer Hardware and Operating Systems, Algorithm Design and Analysis.
    • Statistics: Statistical Inference, Probability, Sample Surveys, Statistical Modeling.

    Volunteer

    • Volunteer Research Assistant at NINET Lab