Software Engineer Machine Learning

Hang Zhao

*************@*****.*** www.linkedin.com/in/allenzhao05/ Boston, MA, 02115

https://github.com/AllenZhaoHang/Allen_Repository/tree/master EDUCATION

Northeastern University Boston, MA

Master of Science in Computer Science GPA: 3.83/4.0 Sept. 2023 – Dec. 2025 Anhui University Hefei, China

Bachelor of Science in Physics

SKILLS

Languages: Java, Python, C Databases: MySQL, Oracle, MongoDB Frameworks: SpringMVC, SpringBoot, React Cloud and Tools: AWS, Azure, Atlassian, Git, GitHub Courses Taken: Discrete and Data Structures, Object-Oriented Design, Data Structures, Algorithms AI and Machine Learning: PyTorch, TensorFlow, LLMs, matplotlib, numpy, pandas Soft Skills: Analytical Critical Thinking, Innovative Problem-Solving, Collaborative Teamwork, Effective Communication EXPERIENCE

PayPal Beijing, China

Software Engineer & QA Engineer Aug 2021 – Aug 2023

• Collaborated with senior cross-disciplinary teams to conceive, design, and launch innovative products and services, ensuring market relevance and satisfaction.

• Leveraged modern programming language Java Python and object-oriented design principles to create solutions for running predictions on distributed systems.

• Participated in all aspects of software development activities, including design, coding, code review, testing, bug fixing, and code/API documentation.

• Collaborated with engineers and participated in daily or weekly stand ups and meetings.

• Participated in peer code reviews to maintain high code quality standards and foster knowledge sharing within the team.

• Effectively addressed technical challenges in a fast-paced work environment, ensuring smooth project progress.

• Worked in an agile environment to deliver high-quality software solutions. GienTech Beijing, China

Software Engineer Jan 2019 – Aug 2021

• Progressed through roles, demonstrating expertise in bank development protocols and business logic.

• Collaborated with the business team to troubleshoot and resolve online issues, conducting joint debugging and testing of deposit products.

• Led the development and enhancement of export API interfaces for deposit products, including the E-Loan online loan product interface.

• Directed a pivotal project for Zhongguancun bank, defining specifications, overcoming challenges, and engaging in PRD reviews.

PROJECTS

PayPal RMB Transfer GraphQL, Pipeline, Github, Linux, Jenkins, Splunk, Jira

• Oversaw the end-to-end testing process of the cross-border RMB payment product, from requirement analysis to test case development.

• Identified and resolved online issues to ensure a seamless product launch. PayPal P2P Pytest, Kafka, SpringMVC, Docker, REST APIs

• Acquired test methodologies and tools, executed test plans, and reported on progress and challenges in regular meetings.

PERSONAL PROJECTS

Imitate QQ Music React, Js, Css, Html (GitHub https://reurl.cc/7078eD)

• A music streaming application built using the React framework mimics the functions and interface of QQ Music. The project aims to provide a modern, responsive user experience while demonstrating the power and flexibility of React technology.

Driving School Management System Java, Springboot, MySql, Maven, Tomcat, React, Vue, ElementUI

(GitHub https://reurl.cc/VzNxEZ)

• Utilized Java and Spring Boot for backend development.

• Implemented MySQL for database management.

• Integrated front-end technologies such as React, Vue, and ElementUI.

• Enhanced operational efficiency and user experience of the driving school.

• Developed comprehensive skills in backend development, database design, front-end framework application, and system integration.

Cats vs Dogs Recognition Tensorflow, Numpy, Matplotlib, Python (GitHub https://reurl.cc/Ke4W6n)

• Developed neural network model for image classification in model.py.

• Organized datasets into test and train subsets in data folder.

• Used input_data.py to read data and generate batches.

• Utilized training.py for model training and evaluation, saving parameters in log folder.

• Managed training and prediction images in image folder.

• Implemented test.py to predict cat or dog from test set.

• Utilized Python, TensorFlow, or PyTorch for development.

• Managed data using custom scripts like input_data.py.

• Used training.py and test.py for model training and testing. Handwritten Digit Recognition Matplotlib, Python, Torchvision (GitHub https://reurl.cc/z1la5p)

• Developed a handwritten digit recognition project.

• Installed necessary libraries: numpy, torch, torchvision, matplotlib.

• Ran the project using python test.py.

• Downloaded MNIST dataset during the initial run.

• Maintained an open network during the first run. Linear Regression Machine Learning, Matplotlib, Numpy, Python (GitHub https://reurl.cc/qVrR6g)

• Implements simple linear regression using gradient descent.

• Global variables are used for parameters like learning rate and convergence threshold.

• Generates a random dataset and calculates the hypothesis function's output.

• Iteratively updates the parameters until convergence in the main loop.

• Employed Matplotlib to visualize the dataset and the fitted linear function.

• User interaction allows running the regression algorithm and viewing the results.

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