Hong Yang

Machine Learning Engineer at Thread

Hong Yang has a diverse range of work experience in various industries. In 2012 and 2013, they worked as an Operations Associate at Heritage Education Funds Inc. and as a Postal Office Clerk at Canada Post. From 2013 to 2015, they held positions as a Sales Associate and Keyholder at The Source and as a Customer Service Analyst and Representative at Roadpost. In 2016, they transitioned to an executive role at Main and Local after working as an Accounting Consultant there. At Main and Local, their responsibilities included initiating and maintaining client relationships, integrating different platforms, automating reporting using VBA macros, and providing tax planning advice. In 2017, they also worked as an Accounting Consultant at another company called Hong Yang. From 2016 to 2020, they worked at L3 WESCAM as a Business Intelligence Developer, where they were involved in various projects related to business intelligence strategy, architecture design, deployment process, and evaluation of BI products. In 2021, they worked as a Research Assistant at the Rochester Institute of Technology and currently serve as a Machine Learning Engineer at Airtonomy, where their responsibilities include implementing ML pipelines, designing pipeline architecture, and implementing automated testing frameworks.

Hong Yang's education history is as follows:

From 2021 to 2025, Hong Yang attended the Rochester Institute of Technology, pursuing a Doctor of Philosophy (PhD) degree in Computer Science.

Between 2019 and 2021, Hong Yang studied at the Rochester Institute of Technology, obtaining a Master of Science (MS) degree in Data Science.

From 2011 to 2016, Hong Yang attended the University of Toronto - Rotman School of Management, earning a Bachelor of Commerce (BCom) degree with a specialization in Accounting.

In addition to their formal education, Hong Yang also obtained two certifications. In March 2019, they completed the Deep Learning Specialization from Coursera. They also completed the Applied Data Science with Python Specialization from Coursera in January 2019.

Links

Timeline

  • Machine Learning Engineer

    June, 2021 - present