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 .

Backend Engineer, Underwriting

Pylon · Palo Alto

About Pylon

America’s $13T mortgage market is one of the most important financial systems in the world. It underwrites the middle class and is the mechanism through which millions of families build wealth. But while every other financial instrument has been simplified to an API call, mortgages are still assembled by hand.

We started from zero and created the first vertically integrated mortgage platform that turns origination into a single API.

Publicly traded companies and the country’s largest originators are already building on Pylon. Revenue is compounding monthly. We’re backed by Peter Thiel, Conversion Capital, QED, Citi, Fifth Wall, and the founders of Ramp, Blend, and Mercury.

Working at Pylon isn’t for those seeking comfort. The people who thrive here have high agency, strong opinions, and a track record of delivering outcomes without direction. Many of us are former founders. We move quickly, challenge each other directly, and take full ownership of results. It’s hard work, but it will be worth it.

Join us in building America’s mortgage rails.

The Team

We're looking for Back End Engineers to join our Underwriting team. This is the team that takes human judgment out of mortgage origination — and replaces it with systems that are faster, more consistent, and more accurate than any human process could be.

Mortgage underwriting today is mostly manual. Experts read guidelines, interpret rules, cross-reference documents, and make decisions that determine whether someone gets a home. We're encoding all of that into software. Nobody has fully cracked this yet. The companies that figure it out will define the next generation of lending.

The stakes are real. An incorrectly modeled rule can cost the company tens of thousands of dollars on a single loan. A well-modeled system can help us outcompete everyone in the market.

Here Is What You'll Do

  • Encode natural language rules into code. You'll work with DSLs and novel techniques — including AI — to translate dense regulatory guidelines into executable logic. Think of it as compiling English into a system that makes six-figure decisions.

  • Work side-by-side with mortgage experts. You won't be guessing what the rules mean. You'll pair with people who've spent their careers in mortgage to understand nuance, exceptions, and the "it depends" that makes this domain so hard.

  • Build systems where correctness is everything. This isn't a domain where "close enough" works. You'll design for precision, build robust test coverage, and think deeply about failure modes.

  • Push into uncharted territory. We're applying AI in ways the mortgage industry hasn't seen. You'll help define what's possible — not just implement what's been done before.

  • Automate complex, regulated processes. Every rule you encode is a step toward a world where mortgages are faster, cheaper, and more accessible.

Tech Stack

  • TypeScript

  • Custom DSLs for rule encoding

  • AI/ML tooling and agentic infrastructure

  • NestJS + GraphQL

  • SQL (PostgreSQL)

  • Temporal.io (workflow orchestration)

Who Will Succeed Here

Someone who:

  • Is deeply curious

  • Wants to won features from design to development to deployment to maintence

  • Is willing to put the work in to solve the hardest of problems

Location: Palo Alto , CA Base Salary Range: $140,000/yr to $220,000/yr + Equity + Benefits