Day 1 Automating the Job Hunt: Battling Spam Detection and the Gender Field Nightmare

https://github.com/cloudhighfive/alphajob

I began working on a new project which targets the developer problem of handling endless job application tasks. The process of completing forms on Lever, SmartRecruiters, and Greenhouse requires full-time dedication because it takes up that amount of time. I began developing this solution during the previous day.

The solution requires advanced techniques for web scraping and browser automation to solve this complex technical problem.

Code Strategy & What's Done So Far:

• The system uses Playwright for browser control to enable smooth navigation between different ATS platforms through a Python-based framework.

• The system uses separate modules for each major platform including Ashby and Workable to handle URL and form field extraction tasks.

• The system successfully detects and fills all typical application fields which include name, email, and basic work history information.

The Current Grind (Technical Issues Requiring Refinement):

1. The system faces two main challenges because it triggers aggressive spam filters which Playwright's built-in stealth features fail to prevent. The system needs to learn how to hide headers and create fake human-like submission delays to defeat complex bot detection systems.

2. The selection process for gender or demographic options proves to be a major stability issue because it seems like a basic operation. The different application forms use inconsistent HTML tags and hidden containers and unreliable CSS selectors which makes my element identification system unstable.