and the web for continuous growth.
Zach Riane Machacon is a proficient software and machine learning engineer with a robust educational foundation in Computer Engineering from the University of San Carlos. His leadership acumen is evidenced by his transformative role in expanding the Google Developer Student Clubs - San Carlos. In his professional journey, he has adeptly navigated the realms of web development and machine learning, demonstrating a commitment to excellence through his contributions to projects like Project Taytayan and innovative research endeavors. With a penchant for data organization and an eye for detail, Zach's methodical approach to problem-solving and project execution sets a high standard within the technology sector.
Data Analysis and Machine Learning
Web Development
Frontend
Backend
Mobile Development
Database and Storage
Other Technologies
Languages
.CZEmcGH9_ZxNAH0.svg)
Cloud Platforms
UI/UX
Software Engineer
Symph
Cebu City, Philippines (Remote)
- Built responsive React components and UI for M Lhuillier, improving transaction workflows and customer experience.
- Developed RESTful APIs and services with Express.js, enabling seamless frontend-backend integration.
Software Engineer
Norg.ai
Melbourne, Australia (Remote)
- Built efficient task pipelines using FastAPI, TaskIQ, and Redis for web crawling, document ingestion, and real-time notifications.
- Designed and implemented React components with Storybook for an internal library, enhancing design consistency.
- Optimized prompts with OpenAI GPT, Meta Llama, and Anthropic Claude models, improving LLM accuracy and relevance.
- Built full-stack features for assistant creation with templates, enabling customized classification workflows with LLMs.
Lead Developer
Gard Technologies
Lexington, Kentucky, USA (Remote)
- Designed and implemented intuitive, responsive mobile interfaces using React Native for 3,000+ active users.
- Built and maintained admin-side web applications with Next.js serving 8 security agencies and 38 client locations.
- Created an in-house invoice generation system which reduced errors in receivables by 10%.
- Integrated OpenAI API functionalities for RAG features for location assistants and report summaries.
Client Success Intern
Dashlabs.ai (YC W21)
Manila, Philippines (Remote)
- Spearheaded B2C communications for prompt issue resolution and enhanced satisfaction.
- Managed meetings and reports for B2C analytics, optimizing strategies.
- Contributed to lead generation and client base expansion through effective marketing.
Image Classification of Omnivores and Herbivores using the CIFAR-100 Dataset
- The project aims to classify images into two categories: omnivores and herbivores, utilizing the CIFAR-100 dataset.
- After 300 epochs of initial training and transfer learning, the model yielded testing accuracy of 0.79, accompanied by a testing loss of 1.53.
Project Taytayan - A Centralized Hub for Trainings and Jobs
- The web application provides a platform for users to register for different local trainings.
- The web application also provides a means for training centers and professionals to help open up employment opportunities for out-of-school youth within the local community through upskilling.
- This project was submitted to the 2024 Google Solutions Challenge.
Accred - An On-demand Event E-Certificate Generator Web App
- Accred automates the certificate generation process and eliminates the need for storing them in the cloud.
- It generates certificates on-demand, ensuring that no unnecessary data is stored and saving valuable storage space.
- Used in PyCon PH 2024, and in Google Developer Student Clubs - University of San Carlos events.
Singapore Exchange Derivative Downloader
- A Python script which downloads daily derivatives from Singapore Exchange.
- It accepts Linux commands and config files.
Predicting Filipino Students' Employability Based on Mock Interview Results
- A machine learning project predicting Filipino Student employability through Mock Interview Results using Logistic Regression, K-Nearest Neighbors, and Support Vector Machine.
- KNN Clasification managed to get the highest accuracy at around 87%, followed by SVM (RBF) at 86%, Logistic Regression at 60%, and SVM (Linear) at 59%.
Gender and Economic-centric Approach on Life Satisfaction
- Concluded that based on the Pearson Correlation Coefficient, GDP per capita and suicide rate have a very weak, negative linear relationship. This shows that suicide rates are not heavily correlated with the economic status of the country.
- It is proof that suicide can happen in first-world or third-world countries and that the risk of suicide is probable to anyone without relation to their status.
Interested in collaborating or have a machine learning project in mind? I'm always open to discussing new opportunities and ideas.
Open to ML Collaborations
Interested in collaborating on machine learning research or projects? I'm currently available for innovative partnerships in this field.