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    <title>DEV Community: mini mac</title>
    <description>The latest articles on DEV Community by mini mac (@mini_mac_8047c3864fcf1125).</description>
    <link>https://dev.to/mini_mac_8047c3864fcf1125</link>
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      <title>DEV Community: mini mac</title>
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      <title>We built a job board that shows salary on every listing. Here's what we learned.</title>
      <dc:creator>mini mac</dc:creator>
      <pubDate>Sat, 02 May 2026 16:30:45 +0000</pubDate>
      <link>https://dev.to/mini_mac_8047c3864fcf1125/we-built-a-job-board-that-shows-salary-on-every-listing-heres-what-we-learned-2je4</link>
      <guid>https://dev.to/mini_mac_8047c3864fcf1125/we-built-a-job-board-that-shows-salary-on-every-listing-heres-what-we-learned-2je4</guid>
      <description>&lt;p&gt;Two years ago I was job hunting and hit the same wall everyone hits: most listings don't show salary. You apply, do a phone screen, do a technical interview, and 4 hours of your life later you find out the budget is 30% below what you needed.&lt;/p&gt;

&lt;p&gt;So we built &lt;strong&gt;Koalaified&lt;/strong&gt; — a job board for tech professionals that shows a salary range on every listing. Either the employer's disclosed range, or a clearly-labeled market-rate estimate when they don't disclose.&lt;/p&gt;

&lt;p&gt;Here's what we learned building it.&lt;/p&gt;




&lt;h2&gt;
  
  
  The data problem is harder than it looks
&lt;/h2&gt;

&lt;p&gt;The obvious approach: aggregate job listings, extract salary data when it exists. But only ~40% of listings in our dataset include an explicit range. For the other 60%, we built a model that estimates salary based on role title, seniority level (extracted from the JD), location, and company type — cross-referenced against BLS occupational stats.&lt;/p&gt;

&lt;p&gt;The key UX decision: always label which type of salary is shown. Employer disclosed vs. our estimate. Trust requires honesty about uncertainty.&lt;/p&gt;

&lt;h2&gt;
  
  
  Ghost jobs are a massive problem nobody talks about
&lt;/h2&gt;

&lt;p&gt;A significant percentage of open job postings are "ghost jobs" — listings that will never be filled. They exist for pipeline-building, compliance theater, or just neglect.&lt;/p&gt;

&lt;p&gt;We built an auto-expiry system: any listing older than 30 days without employer re-verification gets removed. Users loved it. The signal-to-noise ratio improved dramatically.&lt;/p&gt;

&lt;h2&gt;
  
  
  The stack, since people always ask
&lt;/h2&gt;

&lt;p&gt;React + Vite frontend. Node.js backend. SQLite (yes, really — fast enough, dramatically simpler than Postgres at our scale). Single DigitalOcean droplet, Docker Compose. We scrape 35+ ATS platforms (Greenhouse, Lever, Ashby, Workday, etc.) hourly. Infrastructure cost: ~$12/month.&lt;/p&gt;

&lt;h2&gt;
  
  
  What job seekers actually want
&lt;/h2&gt;

&lt;p&gt;After talking to hundreds of users, three things dominate:&lt;/p&gt;

&lt;ol&gt;
&lt;li&gt;
&lt;strong&gt;Salary upfront&lt;/strong&gt; — the frustration about opacity runs deeper than we expected&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;No spam&lt;/strong&gt; — users had abandoned LinkedIn because they couldn't distinguish real opportunities from recruiter noise&lt;/li&gt;
&lt;li&gt;
&lt;strong&gt;Freshness&lt;/strong&gt; — nothing worse than spending time applying to a role that's already filled&lt;/li&gt;
&lt;/ol&gt;

&lt;h2&gt;
  
  
  Check it out
&lt;/h2&gt;

&lt;p&gt;Koalaified is free for job seekers, always. 12,000+ active US tech jobs, updated hourly.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;&lt;a href="https://koalaified.com" rel="noopener noreferrer"&gt;koalaified.com&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;




&lt;p&gt;&lt;em&gt;Building something similar or have questions about the scraping architecture / salary model? Drop a comment.&lt;/em&gt;&lt;/p&gt;

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      <category>career</category>
      <category>webdev</category>
      <category>startup</category>
      <category>javascript</category>
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