Chunfeng Li Email & Phone Number

Toronto, Ontario, Canada

Toronto, Ontario, Canada

• Creating tools and testplans to validate features and performance for ML models that are rewritten in C++ and Python.
• Models in the modelzoo include LLMs such as GPT3, BERT and Llama 3

Waterloo, Ontario, Canada

• Created and deployed, using Jenkins, data ingestion pipelines on Azure DataFactory using the MDMF (Metadata Driven Management Framework) toprocess internal data for consumption automatically on daily intervals
• Coordinated between several teams to oversee and manage the changemanagement process to ensure organised deployments to production
• Used Pyspark to perform large-scale Parallelized data processing in adistributed environment to manipulate SQL data to conform to regulations

Toronto, Ontario, Canada

• Collaborated within the bank-wide Quartz Python workspace to addmultiple features to improve the functionality and usability of ourapplications that are used by traders within Bank of America
• Implemented a multithreaded regression test harness for our application,effectively managing concurrent calls to a grid computer and ensuring theprevention of errors in the Sandra Global Object Database caused.
• Utilized pandas to compile equity ticker data from multiple upstreamsources, enabling the provision of accurate data for applications

Toronto, Ontario, Canada

• Modified the existing AzureML pipeline and its scripts to detect newsymbol objects for clients and reduce memory usage using AMP
• Created and designed a new AzureML pipeline that facilitates the fastretraining of the trained detectron2 object detection model to cut downtraining time for new client data by over 50%
• Redesigned the existing pipeline to allow for modification of trainingconfigurations such as layer freezing and different training data weights
• Using the new retraining workflow, increased previous detection 2 symboldetector model recall on general data by 2% and precision by 5%

Toronto, Ontario, Canada

• Trained and Tested TensorFlow mobile net object detection and yolov5models to improve on the existing Greeter AI app model on the App Store
• Analyzed client data from deployed Greeter AI models to present metricsand insights to clients using Jupyter Notebook, Matplotlib and Pandas
• Designed and created a multi-threaded Cloud inference server in Pythonthat communicates with the Greeter AI app and integrates with GoogleFirestore for storage of client metrics
• Created and tested multiple different prediction models used to predictclient sales using Scikit-learn