JobLens

The JobLens platform revolutionizes the job search experience by leveraging the power of LLMs (Language Model Models) to reformat and unify information from various job postings. Here’s how it works:

Mapping Unstructured Job Postings: JobLens utilizes the capabilities of LLMs to transform unstructured job postings into a unified structure. This process involves reformatting information from any given format X to a standardized format Y. The advanced features of the new GPT (Generative Pre-trained Transformer) model, such as the function functions and extended context windows, prove highly beneficial in achieving this task. This eliminates the need for building a custom Named Entity Recognition (NER) pipeline, as the LLMs handle the mapping process seamlessly.

Customizable Job Sources: While JobLens initially provides job sources, the platform plans to introduce full customization options in the near future. This will enable users to add their preferred companies as sources, ensuring a tailored job search experience that aligns with their specific interests and needs.