EZResume

EZResume Home Page
EZResume Home Page - Feature section
EZResume Form Page
Sample Resume 1
Sample Resume 2

Inspiration

The job application process is often hindered by a tedious hurdle: resume formatting. We realized that job seekers spend more time wrestling with document margins and layout consistency than focusing on their actual content. Furthermore, the need for personalized resumes tailored to specific roles adds a layer of complexity that many find overwhelming. We built EZResume to bridge the gap between raw professional data and high-quality, industry-standard presentation.

What it does

EZResume is an intelligent web application that automates the creation of professional resumes. By taking user-inputted data, the platform leverages AI to generate perfectly formatted LaTeX documents. This ensures that every resume produced is not only visually polished and consistent but also optimized for both human recruiters and automated tracking systems (ATS).

How we built it

Frontend: React and Javascript Backend: Python

Challenges we ran into

One of our primary hurdles was prompt engineering. Striking the right balance to ensure the AI generated valid, compilable LaTeX code while maintaining a professional aesthetic required significant iteration. Additionally, establishing a robust bridge for frontend and backend integration was a key focus, as we needed to ensure that user data flowed securely and efficiently through our processing pipeline.

Accomplishments that we're proud of

We are incredibly proud of successfully integrating our Python backend with the React frontend to create a functional, end-to-end prototype. Seeing a simple text input transform into a beautifully typeset PDF document in real-time was a major milestone for our team. We are also proud of the user privacy we have in place. When generating the resume, we don't provide the AI with private details such as the user's name and email, and instead have the AI generate placeholders that we update afterwards with the private information.

What we learned

Above all, this project reinforced that teamwork makes the dream work. We learned how to synchronize different technical stacks and communicate effectively under the pressure of a hackathon timeline. We also gained deeper insights into the power of AI-driven document automation.

What's next for EZResume

The current version is just the beginning. We plan to implement advanced personalization features, allowing users to request specific stylistic changes or industry-specific templates through natural language prompts, making EZResume the ultimate career-readiness tool.

Built With

Submitted to

HACK THE WU

Created by

I worked on the resume generation, taking user input and creating a PDF file that is tailored to the user submission. I also created the private data protection feature, where the API doesn't see your private data.

Jackson Keeler
I worked on the front end. This was such a fun experience to be collaborating with strangers for a common goal, being to come up with a great idea and actually making it come to life.

Wei Jin
I worked on the back end. I was my first time calling an LLM API and prompting in my terminal. I learned a lot from this event. Thank you so much!

Khang Duong