Ming Liu
Verified Expert in Engineering
AI Engineer and Developer
Singapore, Singapore
Toptal member since June 16, 2021
Ming is a machine learning engineer specializing in recommender and anti-fraud systems. He has been working in data science and AI for the past four years, including building and improving the recommender system for Shopee and TikTok, which have hundreds of millions of users and items. Ming's industry experience is backed by a master's degree in computer science.
Portfolio
Experience
- Python - 5 years
- Deep Learning - 4 years
- Deep Neural Networks (DNNs) - 4 years
- Data Analysis - 4 years
- Recommendation Systems - 4 years
- Machine Learning - 4 years
- eCommerce - 3 years
- Computer Vision - 2 years
Preferred Environment
Linux, PySpark, Python, Keras, TensorFlow, Docker
The most amazing...
...system I've developed was for TikTok, and it's popularity is due, in large part, to the successful recommender system I built.
Work Experience
Machine Learning Engineer
TikTok
- Improved TikTok's live streaming recommendation system by adding multiple retrieval and recall queues.
- Improved TikTok's live streaming recommendation system by using more complex neural networks and adding more concrete objectives and targets for the system.
- Increased TikTok's overall live-streaming revenue by applying multiple revenue strategies, implementing those strategies in the system, and conducting A/B tests.
Senior Data Scientist
Shopee
- Led a team of five (plus two interns) to build and refactor a unique user identification system, which included setting up a graph database and building a data pipeline and business engine.
- Collaborated with team members to build an interactive data dashboard for managers and other colleagues to explore the user-user relationship.
- Assisted team members with improving JanusGraph, an open-source tool, according to business requirements.
Data Scientist
Shopee
- Increased the click-through rate on the homepage recommender system by 50% by using deep neural networks.
- Increased the conversion rate on the shopping cart page by around 20% by using online learning to build a new module called "You may also like."
- Created graph database clusters and used the database to store buyer-seller relationships.
Machine Learning Engineer
XRVision
- Built object detections for CCTV cameras for buildings, factories, and roads, with more than 70% accuracy.
- Developed image classification models for the company's core product that has the general ability to recognize gender, facial hair, eyeglasses, and other features, with an overall accuracy of 90%.
- Built facial recognition models for several companies' check-in systems.
Experience
Enhanced Recommendation System for eCommerce Website
Object Detection for CCTV Cameras
Refactored Unique User Identification System for eCommerce Website
This project helps the company understand which users are highly likely to be fraudsters who created multiple accounts to get benefits. By using Go to replace Python, the system performance improved by 80% in terms of increased speed and decreased memory.
Education
Master's Degree in Computer Science
National University of Singapore - Singpore
Bachelor's Degree in Information Technology
Southeast University - China
Skills
Libraries/APIs
PySpark, TensorFlow, Keras, OpenCV
Tools
Apache Airflow
Languages
Python, SQL, Go, C++
Frameworks
Spark, Flask
Platforms
Linux, Docker, Amazon Web Services (AWS)
Storage
Graph Databases, Neo4j, Elasticsearch
Other
Recommendation Systems, Machine Learning, Deep Learning, Deep Neural Networks (DNNs), Data Analysis, Data Visualization, Data Structures, Algorithms, Neural Networks, eCommerce, Computer Vision, Anti-fraud, Object Detection, Facial Recognition, Team Leadership, System Design
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