Structured, real-world job data for training recruitment and labor market models
Synthetic job data has a ceiling. Models trained on it learn patterns that don't reflect how employers actually write job descriptions, structure requirements, or signal seniority. CleanJobData provides real job listings sourced directly from employer ATS systems — consistently normalized, commercially licensed, and available at scale. Whether you're training a job matching model, a salary prediction system, a skills extraction pipeline, or a labor market forecasting tool, you're working with data that reflects how the actual market behaves.
Yes — our standard terms permit use in commercial AI and ML products including job matching algorithms, salary prediction models, and recruitment automation tools. Review the full terms at cleanjobdata.com/terms.
Real data, sourced directly from employer career pages via Greenhouse, Lever, Ashby, and Workable. These are live job postings from companies actively hiring — not generated or augmented examples.
For a one-time snapshot, page through next_page cursors on a filtered query until you've pulled every matching row. For a dataset that keeps growing, run a recurring job with created_max_age (e.g. created_max_age=1d run daily) so each run pulls only the listings ingested since the last one. For large historical backfills, contact us at cleanjobdata.com/support.
Yes — GET /jobs/:id always includes the full description automatically. List responses exclude it by default to keep payloads light; add extra_fields=description to a list query to get it inline instead of making a detail request per row, which is the faster path when you're bulk-collecting description text for NLP training.
Run your pipeline on a schedule with created_max_age set to match the interval — created_max_age=1d for a daily job, created_max_age=7d for weekly. It filters on ingestion time (when CleanJobData indexed the listing), not the employer's published date, so each run picks up only what's new since the last one without re-downloading the full index.
