Software Engineering Engineer

Shuxin Yang

EDUCATION 206-***-**** *********@*****.*** Linkedin Seattle, WA

Northeastern University Seattle, WA, USA

Master of Science in Computer Software Engineering (GPA:3.88/4.0) Sep 2024 - Jun 2026 Courses: Web Development, Databases, Data Structures & Algorithms, Object-Oriented Design, Machine Learning Seattle Central College — Seattle, WA, USA — Computer Science coursework (Mar 2024 – Aug 2024) Soonchunhyang University Chungcheongnam-do, South Korea Bachelor of Science in Computer Software Engineering (GPA: 3.84/4.0) Sep 2019 - Mar 2022 Honors: Received multiple academic excellence scholarships based on merit (2019–2021) SKILLS

Languages: Python, Java, C/C++, JavaScript, TypeScript, SQL, HTML/CSS Database: MySQL, Redshift, PostgreSQL, MongoDB, DynamoDB Frameworks & Tools: Spring Boot, Django, Flask, Node.js, Express, React.js, Linux, Git, Docker, Kubernetes, AWS (EC2, S3, RDS, Lambda, API Gateway, SQS), Kafka, CI/CD, Jenkins, Junit WORK EXPERIENCE

Software Engineer Intern Jun 2023 - Nov 2023

ByteDance Beijing, China

● Designed and implemented an automated detection pipeline to monitor potential overload risks in the health status of internal testing IoT devices.

● Scheduled Java-based diagnostic tasks using Kubernetes CronJobs (automated scheduled jobs on Kubernetes) triggered by metric output.

● Utilized RabbitMQ to asynchronously handle and route risk status messages, ensuring decoupled, scalable processing.

● Delivered real-time alerts to endpoint devices via Twilio/SendGrid to endpoint devices, ensuring timely operational responses.

● Built a resilient, event-driven microservices architecture leveraging ByteDance’s internal cloud platform; designed RESTful APIs and automated workflows using CI/CD pipelines.

● Collaborated with product managers and cross-functional teams to define technical solutions, align on requirements, and deliver features on schedule.

PROJECTS

Real-Time Emotion Detection & Image Analysis App Jan 2024- May 2025

● Developed face & emotion detection using OpenCV, TensorFlow/Keras, and C++, running at 30 FPS.

● Simulated an ISP pipeline for image enhancement (color normalization, exposure, noise reduction), improving accuracy under varied lighting.

● Built a Matplotlib dashboard to visualize training metrics and image quality, improving model accuracy by 15%.

● Dockerized the application and deployed to Google Cloud with GPU acceleration for scalable inference.

● Developed unit and integration tests using PyTest and unittest with real-time camera feeds and test image datasets, improving code reliability by 20%.

Full Stack Movie Recommendation Website Jan 2024 - Oct 2024

● Built a full-stack movie recommendation website with secure user authentication, profile management, and personalized recommendations; implemented both frontend and backend logic using modern web stacks..

● Developed backend using Node.js and Express; secured sensitive data with SHA256 encryption.

● Deployed backend services on AWS EC2, RDS for data storage, and integrated S3 to serve movie posters.

● Created responsive frontend using React and Material-UI; implemented features like movie reviews, recommendation logic, and a "watch later" collection.

Fitness Video Streaming Platform Feb 2024 - May 2025

● Designed a seamless data pipeline that combines efficient media streaming, real-time user tracking, and optimized content delivery through AWS services.

● Developed backend services using Java and Spring Boot to handle video streaming transfer for delivering high-quality workout content. Built interactive frontend interfaces with React and Redux to provide a responsive user experience.

● Integrated Amazon S3 for temporary video storage to support scalable and efficient video streaming workflows.

● Collected and logged user interaction data into Amazon Redshift to enable advanced analytics.

● Cached video metadata at CDN edge nodes to accelerate content delivery and minimize playback latency.

● Used Amazon DynamoDB to store user profiles and activity logs in a scalable, non-relational format.

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