New Location Filters for precise geographic targeting in job searches

🚧 Beta Feature: This new filtering capability is currently available for recent jobs (posted within the last 3 months ±). We're actively expanding coverage to older jobs and improving the system based on user feedback. 🚧

We've introduced new location filters job_location_or and job_location_not to the Jobs Search endpoint and Company Search endpoint for precise geographic targeting in job searches.

These new filters address several limitations of the existing location_pattern_or filter:

Greater precision - Target specific cities, states, or regions with exact accuracy. When searching for San Francisco, results will be limited to California, U.S., and won't include other cities with the same name elsewhere in the world
Hierarchical location searches - Search for "Europe", "China" or "California" and get all jobs within that region. The hierarchical location data enables searches at any level (country, state, province, city, etc.). This wasn't possible with the previous text-based approach, which couldn't understand location hierarchies
Multi-language location searches - Search for locations in different languages using the same location IDs, ensuring consistent results regardless of the search language. With the previous string matching approach, searching for "Germany" wouldn't match all occurrences since "Deutschland" could be used instead
Cross-country city searches - Search across multiple cities in different countries simultaneously. This supports state/city queries across countries (e.g., Alabama, US and London, UK) in a single search request
Improved flexibility - Easily combine multiple location criteria or exclude specific areas
Better performance - More efficient searches using indexed location data
Structured data - Uses normalized location IDs instead of text pattern matching

You can use the locations catalog endpoint to search for the IDs of your desired locations.

🚧 Beta Feature: This new filtering capability is currently available for recent jobs (posted within the last 3 months ±). We're actively expanding coverage to older jobs and improving the system based on user feedback. 🚧

We've introduced new location filters job_location_or and job_location_not to the Jobs Search endpoint and Company Search endpoint for precise geographic targeting in job searches.

These new filters address several limitations of the existing location_pattern_or filter:

Greater precision - Target specific cities, states, or regions with exact accuracy. When searching for San Francisco, results will be limited to California, U.S., and won't include other cities with the same name elsewhere in the world
Hierarchical location searches - Search for "Europe", "China" or "California" and get all jobs within that region. The hierarchical location data enables searches at any level (country, state, province, city, etc.). This wasn't possible with the previous text-based approach, which couldn't understand location hierarchies
Multi-language location searches - Search for locations in different languages using the same location IDs, ensuring consistent results regardless of the search language. With the previous string matching approach, searching for "Germany" wouldn't match all occurrences since "Deutschland" could be used instead
Cross-country city searches - Search across multiple cities in different countries simultaneously. This supports state/city queries across countries (e.g., Alabama, US and London, UK) in a single search request
Improved flexibility - Easily combine multiple location criteria or exclude specific areas
Better performance - More efficient searches using indexed location data
Structured data - Uses normalized location IDs instead of text pattern matching

You can use the locations catalog endpoint to search for the IDs of your desired locations.