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 .

Senior Software Engineer

Irregular · Tel Aviv

As a Software Engineer at Irregular, you will take ownership of designing, building, and scaling the production systems that power our evaluation and security platform for frontier AI models.

Your work will focus on creating robust, resilient, and high-performance infrastructure—whether that’s distributed pipelines, backend services, or tooling that supports our research teams.

This role is engineering-first with a strong research and cyber component. You will develop systems that must run reliably in production, integrate with external partners, and support large-scale data, experiments, and automated evaluations. You’ll drive architectural decisions, lead technical implementations, and shape how our platform evolves.

Representative Responsibilities:

  • Architecting and scaling production-grade systems and workflows.

  • Building backend services, APIs, and monitoring tools for large-scale model evaluations.

  • Designing infrastructure that supports research experiments at scale.

  • Implementing agent frameworks in production environments

  • Designing and building challenges that measure a model’s ability to evade discovery, allowing us to see if models can operate on remote systems while avoiding detection by common defensive security tools.

You may be a good fit if you:

  • Have strong software engineering fundamentals and multiple years of production experience.

  • Have experience working in multidisciplinary teams, and can adapt to rapidly evolving challenges.

  • Enjoy working at the intersection of engineering and applied research.

  • Are interested in AI and cybersecurity (experience in machine learning or cybersecurity is a plus but not necessary).

  • Care about the societal impacts of your work.