JobsWithPay
JobsWithPay is a tech job board that shows posted pay for 44.3% of roles, reading listings directly from company career sites and checking them daily.
Overview
JobsWithPay is a technology job search platform that publishes compensation alongside listings. The site reports 93,089 open tech roles from 7,793 companies, with 44.3% showing posted pay. Listings are read from company career sites and applicant tracking systems, checked daily, and removed after two consecutive misses. The product serves software engineers, AI and ML specialists, data professionals, product managers, designers, and other tech candidates who want salary visibility before applying. It combines natural language search, pay comparison charts, company coverage data, and portfolio pages built from resumes and public work. JobsWithPay is free in beta and requires only an email address for saved jobs, alerts, and portfolio creation.
Key Features
- Direct company job board ingestion: Reads listings from employers' careers sites and systems such as Greenhouse, Ashby, Lever, Workday, and Workable. It excludes staffing agencies and copycat sites, and shows each job once. The source table lists 36,187 jobs from Greenhouse, 21,875 from Ashby, 10,685 from company careers sites, 9,507 from Lever, and 6,146 from Workday.
- Posted pay visibility: Shows compensation when employers publish it, without estimates or adjustments. The platform reports 44.3% coverage, compared with 18.7% in its LinkedIn sample. Pay charts display median low and high base pay ranges for companies with at least five jobs that include pay.
- Daily freshness checks: Rechecks each job on the company board every day. If a role is absent at two consecutive checks, it is removed. JobsWithPay reports that 93% of open jobs were checked in the previous 24 hours.
- Natural language AI search: Allows candidates to describe a role in plain language, such as remote senior ML positions paying $200K or more. The AI parses intent and returns matching jobs. Common filters include remote, posted pay, entry level, AI/ML, and posted today.
- Pay explorer and company comparisons: Provides interactive charts by job type and location. Users can compare top-paying companies for software, ML/AI, data science, product, and design roles in the Bay Area, New York, and remote US markets. The comparison tool measures pay disclosure, irrelevant results, staffing agency listings, and duplicate jobs against LinkedIn using 18 AI and ML searches.
- Portfolio pages with proof: Builds a public portfolio from a resume and adds evidence from public work such as merged pull requests, repositories, papers, packages, and releases. Each skill is labeled Proven, Stated, or No proof, and recruiters can compare a page against a job in one click. The sample page shows how an inference engineer role maps to specific evidence.
How It Works
JobsWithPay operates as a search layer over employer job boards. A candidate can start with the main search field, type a natural language request, or browse common filters such as remote, posted pay, entry level, AI/ML, and posted today. Results show the job title, company, posted pay range when available, and the date of the latest check. Each listing opens on JobsWithPay, while the apply button leads to the employer's own site. Signed-in users can save jobs and receive job emails. The platform also provides a pay explorer that lets users choose a job type and a place, then view companies ranked by median posted base pay. For portfolio creation, a user signs in with an email address, imports resume details, and the system supplements skills with public evidence. Recruiters can then compare the portfolio with a specific job and see which requirements are proven, stated, or unsupported.
Use Cases
A senior backend engineer who wants remote work in the $200K range can use the natural language search to combine role, location, and salary filters, then scan only listings that show posted pay. A new graduate looking for visa sponsorship in New York can start from the suggested search example and narrow results by entry level and posted date. A data engineer in Bengaluru can search for roles that use Spark and compare local openings with remote US listings. A recruiter or hiring manager can use portfolio comparison to check whether a candidate's public work supports the skills in an open role. A compensation researcher can use the pay explorer to compare median base pay ranges at Netflix, Anthropic, OpenAI, Roku, and other companies, while filtering by job type and region. A job seeker who wants fewer stale applications can rely on the daily check date and the removal rule for closed roles.
Who It's For
JobsWithPay serves tech candidates who value compensation transparency and direct employer listings, including software engineers, ML and AI researchers, data scientists, infrastructure specialists, security engineers, product managers, and designers. It suits job seekers who want to avoid staffing agency posts, duplicate listings, and stale roles. Compared with LinkedIn and broad aggregators, the platform is narrower and more transparent, though coverage is limited to tracked companies and job boards.
Pros & Cons
The Good
- Reads job listings directly from company career sites and applicant tracking systems, then checks them daily to reduce stale or duplicate postings.
- Shows posted base pay on 44.3% of listings, a higher disclosure rate than the 18.7% measured for LinkedIn in the site's own comparison.
- Natural language AI search lets candidates describe role, location, and salary goals in plain English.
- Portfolio pages add public evidence to resume skills and label each requirement as proven, stated, or no proof.
- Free during beta with email sign in, job alerts, pay explorer, and comparison tools.
The Bad
- Only 44.3% of listings include posted pay, so most roles still require compensation research outside the platform.
- Coverage focuses on technology jobs and selected companies, and some large employers rely on a weekly paid feed rather than daily direct checks.
- Portfolio proof depends on public work, which may disadvantage candidates without open source, papers, or public packages.