ai-linkedin-applier

The AI LinkedIn Applier which adjusts your Resume based on the job descripton provided -- updating the Projects & Technical Skills Section of your Resume 🔥

The AI scraper will:

1. Go through job postings one-by-one on LinkedIn.
2. Read the job description of the posting, and send it the LLM.
3. The LLM will output a new Projects & Technical Skills section for your Resume in Latex format.
4. The LLM output will get pasted on your Resume, on Overleaf -> and will recompile & save your new Resume as a PDF.
5. The scraper will go back to LinkedIn and apply to the job with your new Resume 💎
6. The scraper will give you 60 seconds (adjustable in the code), to fill out any additional questions on the LinkedIn application.
7. Once you click Submit application you don't need to do anything else, steps 1-6 will repeat on auto-pilot 😎.

Everything was built live on stream 🔥

Simple Pre-requisites

1. Ollama. For running the LLM locally on your machine. Note: I may make a separate branch which uses HuggingFace for the LLM call.
2. A Resume on Overleaf which follows the popular Jake's Resume Format.

How to Run:

1. Run chrome in Debug mode:

/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome --remote-debugging-port=9222

Adjust to the location of your Chrome.

2. Open your tabs:

1. Open LinkedIn -> go to Jobs -> go to the Easy Apply category.
2. Open Overleaf on your Resume.

• Note: The order in which you open your tabs is important. Open LinkedIn first, and Overleaf second.

3. Set your ENV variables:

Set the follow variables in your .env file.

• DOWNLOAD_DIR: the absolute path to your Downloads directory.
• PHONE_NUMBER: your phone number (Easy Apply applications usually ask for this).
• CHROME_DRIVER_PATH: the absolute path to your chrome webdriver.

4. Run the Scraper

pip install -r requirments.txt 

python scraper.py

Now go and secure those job offers 💪