Software Engineering Mountain View

ZILONG GUO

Mountain View, CA 949-***-**** *******@******.***.*** LinkedIn GitHub

EDUCATION

Carnegie Mellon University Silicon Valley Campus, CA Master of Science in Software Engineering August 2024 - December 2025 Relevant Courses: Software Engineering, Software Management, Functional Programming, Computer Systems University Of California Berkeley Berkeley, CA

Bachelor of Arts in Computer Science June 2022 - May 2024 Relevant Courses: Structure & Interpretation of Computer Programs, Data Structures, Computer Architecture, Web Design, Computer Security, Internet Architecture & Protocols.

SKILLS

Programming Languages: Java, Python, JavaScript, CSS, C, C++, Ruby, SQL, Go, MATLAB, and Scheme Techniques: Git version control; OOP; Linux System, Google Cloud Platform Tools: Visual Studio Code, IntelliJ IDEA, Rider, Jupyter Notebook, MATLAB, XGBoost, Scikit-learn, BigQuery, Word, Excel, PowerPoint EXPERIENCE

TMind AI Mountain View, CA

Researcher & Software Engineering (Tech Lead)May 2025 - Present Lead developer in the core team for an AI-powered mental health training platform, combining full-stack engineering with AI/ML research to bridge modern technology and therapy education.

● Full-Stack Systems Development: Delivered responsive, production-grade apps with React 19 (Next.js 15), TypeScript, Tailwind, and Framer Motion, supported by Node.js (Express) microservices, Docker, and WebSocket for real-time interaction.

● AI & ML Integration: Integrated OpenAI GPT, Azure OpenAI, and LangChain for conversational AI; added Deepgram speech-to-text; designed AI-powered client profile generation and real-time conversation management.

● Database & Cloud Migration: Managed PostgreSQL (Neon) with Prisma ORM and Redis; led data migration to GCP, optimizing schemas, caching, and query performance.

● Security & DevOps: Built Clerk-based authentication with JWT/role control; established CI/CD pipelines using GCP Cloud Build for automated testing and deployment.

● Research & Algorithm Development: Conducting research into patient–therapist matching systems, designing algorithms that combine text-to-text semantic matching (Sentence-BERT, TrialGPT-style LLMs) and hybrid models (structured + unstructured data). Responsible for data collection, model training, evaluation, and integration into the production platform.

● Product Impact: Delivered key features—AI client creation, voice training sessions, course management, group therapy simulations, and AI-driven analytics—enabling therapists, students, and healthcare organizations to train in safe, scalable environments.

Henan Broadcasting System Remote

Data Science & Software Systems Engineer intern May 2023 - August 2023

● Designed and deployed scalable MySQL relational database architecture, including ER modeling, schema normalization, and query optimization for the high-traffic "China Festival" series, resulting in over 67.42M global views.

● Developed Python automation scripts with Pandas and SQLAlchemy for test environment orchestration, performance bottleneck analysis, and DB performance tuning; integrated reporting with Matplotlib and Seaborn for visualization.

● Developed a machine learning pipeline to process and analyze a high-dimensional dataset (4,000+ features), applying dimensionality reduction (PCA) and feature selection techniques (L1 regularization, mutual information). Trained and compared a comprehensive set of models — Logistic Regression, SVM, Random Forest, Gradient Boosting (XGBoost), and Neural Networks — achieving high predictive accuracy. The results provided actionable insights that guided the creative direction and theme selection for high-performing video content.

● Applied Agile/XP practices with daily standups, pair programming, and TDD in a SOA environment; refactored legacy Python and Node.js services, enhanced SaaS performance and security, and wrote BDD-style user stories. PROJECTS & RESEARCHES

Ad Timing Optimization: Machine Learning for Enhanced Mobile Ad Delivery CMU, January 2025 - May 2025

● Built predictive analytics pipeline with XGBoost and TensorFlow (LSTM) to optimize mobile ad placement timing, analyzing temporal engagement patterns and increasing predicted CTR by 24%.

● Engineered feature extraction for time-series logs via BigQuery SQL; applied K-means and DBSCAN clustering to identify engagement archetypes.

● Developed Flask API real-time scoring system for dynamic recommendations; validated across multiple BigQuery-hosted gaming datasets for robust generalization.

Emergency Social Network, Software Engineering Project CMU, August 2024 - December 2024

● Led back-end development of an emergency-response social platform using Java, Spring Boot, MySQL, MVC architecture, and Agile/Scrum.

● Implemented CI/CD with GitHub Actions and Jenkins; wrote unit/integration tests in JUnit/Mockito achieving 90%+ coverage.

● Applied OOD, UML, and design patterns (Factory, Observer, Singleton) to deliver maintainable, modular systems; facilitated API design and peer reviews for cross-team collaboration. Pacman Game with AI Berkeley, CA, Jan 2023 - May 2023

● Enhanced AI agents in Python using algorithms such as A* search, CSP, Minimax with Alpha-Beta Pruning, MDP, Q-Learning, HMM, and Reinforcement Learning, improving performance by 30%.

● Applied probabilistic reasoning, state-space search, and policy optimization; used NumPy and Matplotlib for iterative development, debugging, and performance tuning.

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