Key Takeaways

  • 75% of U.S. employers use automated applicant tracking systems to screen resumes before a human reviews them (Harvard Business School & Accenture, 2021)
  • The most common ATS failures are missing keywords, incompatible formatting, and incorrect file types
  • ResumeGeni scores your resume across 8 parsing layers — modeled on the same steps enterprise ATS platforms like Workday, Greenhouse, and Taleo use to evaluate candidates

How ATS Resume Scoring Works

Applicant tracking systems parse your resume into structured data — extracting your name, contact info, work history, skills, and education — then score how well that data matches the job requirements. Many ATS rejections happen because the parser couldn't extract critical fields, not because the candidate wasn't qualified.

LayerWhat It ChecksWhy It Matters
Document extractionFile format, encoding, readabilityCorrupted or image-only PDFs fail immediately
Layout analysisTables, columns, headers, footersMulti-column layouts break field extraction
Section detectionExperience, education, skills headingsNon-standard headings cause sections to be missed
Field mappingName, email, phone, dates, titlesMissing contact info is a common cause of immediate rejection
Keyword matchingJob-specific terms, skills, certificationsKeyword overlap affects recruiter search visibility and ATS scoring
Chronology checkDate ordering, gap detectionReverse-chronological order is expected by most ATS
QuantificationMetrics, numbers, measurable outcomesQuantified achievements help human reviewers and some scoring models
Confidence scoringOverall parse quality and completenessLow-confidence parses get deprioritized in results

Frequently Asked Questions

Is ResumeGeni free?
Yes. ResumeGeni is currently in beta — ATS analysis, scoring, and initial improvement suggestions are free with no signup required. Full guidance and saved reports may require a free account.
What file formats are supported?
PDF, DOCX, DOC, TXT, RTF, ODT, and Apple Pages. PDF and DOCX are recommended for best ATS compatibility.
How is the ATS score calculated?
Your resume is processed through an 8-layer parsing pipeline that extracts structured data the same way enterprise ATS platforms do. The score reflects how completely and accurately your resume can be parsed, plus how well your content matches common ATS ranking criteria.
Can ATS read PDF resumes?
Yes, but not all PDFs are equal. Text-based PDFs parse well. Image-only PDFs (scanned documents) and PDFs with complex tables or multi-column layouts often fail ATS parsing. Our analyzer will flag these issues.
How do I improve my ATS score?
Focus on three areas: use a clean single-column format, include keywords from the job description naturally in your experience bullets, and ensure all sections (contact, experience, education, skills) use standard headings.

ATS Guides & Resources

Built by engineers with 12 years of experience building enterprise hiring technology at ZipRecruiter. Last updated .

Opportunity Hire, ex-founder/founding engineer

Safariai · North America

About Safari AI
Safari AI's vision is to Automate Action of the leading companies in the physical economy, from Entertainment, Live Venues, QSR's, Retail and beyond. The company uses computer vision AI to Measure, Alert and provide AI-generated Recommendations at the operations of leading enterprises such as Merlin/Legoland, 7-11, Tanger Outlets, Charlotte Hornets, Calgary Flames, and more. This year, Safari AI's platform will begin to use this data and to suggest to clients how they can optimize their operations to generate higher throughput, more revenue and optimize staff deployment.
 
Safari AI is venture-funded and expects to raise its Series A in 2026.
 
Leadership & Culture
Safari AI is co-founded by Ali Vahabzadeh & Kaiwen Yuan, two leaders who have meaningful exits under their belts and have managed large, high-performing Go To Market and Engineering teams. The company is headquartered in Miami with the Engineering team based in Vancouver with some distributed team members.
 
About You And How You Succeed At Safari AI
You're excited about building a product and creating a market that hasn't been done before. You have a strong bias toward action when you are stuck but are not afraid to ask for help when you need to. You're a high agency contributor, eager to test new ways of doing things and take advantage of the freedom and culture an early stage startup can afford you. You want to lead the company's engagement with category leaders in a variety of industries, solving some of their biggest challenges.

We always welcome unicorn engineering talents to join us!

This opportunity hire is specifically for ex-founder or ex-founding engineer! 

What you must have

  • previous startup founding team (founder or founding engineer) experiences
  • previous big enterprise experiences
  • depth knowledge in modern AI and data engineering
  • at least 5-8 years software individual contributor experiences
  • proficiency in cloud infrastructure
  • proven record of leadership on building a complex service from scratch to production
  • experiences in delivering incremental features and maintaining reliabilities of a production service
  • good understanding in best practices in software development lifecycle (SDLC) and security compliance

What we provide

  • Opportunity to shape an early-stage, mission-driven startup and revolutionize how Enterprises use Computer Vision
  • Professional growth at a fast-growing, venture-funded start up with a proven founder and leadership team
  • Competitive salary and meaningful equity for early team members
  • Unlimited vacation days
  • Generous health benefits (Health, Vision, Dental)
  • 401k for US team members
  • Brand new, top of the line hardware and whatever else you need to help you win

We are not considering any agent/agency and only matched candidates will be reached out.

Please provide your Linkedin and github link. 

Why bet on Computer Vision and Safari AI? 

  1. Huge opportunity hiding in plain sight: leveraging already-installed cameras to automate and real-time action on operational data
  2. Already the market leader in enterprise CV by working with industry leaders with billions in revenue
  3. Large chasm between customer knowledge and market availability, i.e. customers don't know what is available in the market...yet.
  4. Early leader in computer vision; everyone is small and unbranded (i.e. no Amazon or Google in the room to compete with)
  5. Very modular, allowing Safari AI and its customers to invent whole new use cases on a regular basis
  6. Developed the tech and data pipelines over three years and invested several million dollars and is now ready to scale