Show HN: I built a tool to help freelancers find better Upwork jobs with AI (github.com)

A developer released the source code for "Upwork Opportunity Matcher," an open-source tool that uses AI to help freelancers surface better-fitting Upwork job postings. The repository includes an installation and usage walkthrough video and is organized into two branches: a stable branch that uses a traditional .env configuration for command-line-savvy users, and a work-in-progress branch that will add a user-friendly in-app settings page for people who prefer a graphical interface. The project is positioned as a practical, hands-on utility for improving job discovery on Upwork using automated matching and scoring. For the AI/ML community this is a useful example of applying models to real-world information retrieval and ranking problems—particularly around personalized relevance, feature engineering (skills, rates, job descriptions), and integrating model outputs into user workflows. Key technical takeaways: source code is available for inspection and extension, configuration is flexible (env-based or eventual GUI), and the project invites improvements such as different model backends, fine-tuning for domain-specific matching, and privacy- or compliance-minded data handling. Potential considerations include sourcing/updating job data, adherence to Upwork’s terms, and evaluating model fairness and bias when recommending opportunities.