AI Local Job Finder Prototype
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
The goal is to have a working Android prototype that lets students and other local job seekers discover nearby openings that truly match their skills. A lightweight AI matching engine should suggest roles automatically, then allow users to refine results with built-in filters by location, specific skills, or job type.
I’m aiming for a clean, minimalist interface that gets first-time users to a relevant listing in just a few taps, so keep navigation simple and avoid visual clutter. Fast setup is critical; the build will be showcased at an upcoming hackathon, so an installable APK and source project are both needed.
Core acceptance criteria:
• AI-driven recommendation logic delivers at least three relevant jobs when given a sample profile.
• Manual search returns filtered results for each of the three filter dimensions (location, skills, job type).
• Runs smoothly on a standard mid-range Android phone without extra configuration.
• Clear README covering setup, model or API choices, and how to retrain or tweak recommendations.
Open-source libraries and lightweight frameworks are welcome as long as the final solution stays affordable and easy to extend after the event.
I’m aiming for a clean, minimalist interface that gets first-time users to a relevant listing in just a few taps, so keep navigation simple and avoid visual clutter. Fast setup is critical; the build will be showcased at an upcoming hackathon, so an installable APK and source project are both needed.
Core acceptance criteria:
• AI-driven recommendation logic delivers at least three relevant jobs when given a sample profile.
• Manual search returns filtered results for each of the three filter dimensions (location, skills, job type).
• Runs smoothly on a standard mid-range Android phone without extra configuration.
• Clear README covering setup, model or API choices, and how to retrain or tweak recommendations.
Open-source libraries and lightweight frameworks are welcome as long as the final solution stays affordable and easy to extend after the event.
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