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 .

Founding Fullstack Engineer

Hexa · Paris

Verso is building the Consumer Intelligence OS.

We replace traditional qualitative research agencies with an AI-native platform that conducts, analyzes, and compounds consumer conversations at scale. Instead of one-off studies, companies get a continuous, structured understanding of their customers.

Our ambition is to make consumer insight a real-time, always-on system embedded in every product and marketing decision.

We’re starting with AI-moderated interviews — but this is just the entry point. The long-term product is a system of record for consumer understanding, powered by agentic workflows.

Backed by Hexa (eFounders), behind Aircall, Front, Spendesk, Yousign and 50+ others.

Verso is founded by an experienced team with a strong track record in strategy, technology, and company building.

Lydia - CEO: HEC graduate, 7 years at BCG (Principal), expert in strategy, innovation, and consumer goods

Camille - CTO: Dual degree X/HEC, former lead at CO2 AI, expert in AI and scalable product development

The role

You will join Verso as a Founding Engineer to own systems end-to-end → from infrastructure to product, with no strict boundaries — and help define engineering standards, observability, and the foundations of the team.

You will design and scale a coherent AI system end-to-end, at the intersection of agents, data, and product:

  • An AI interviewer interacting with users at scale (voice & video), sustaining long-form conversations with high reliability

  • Agent systems (state, memory, evaluation loops) orchestrating complex interactions

  • Real-time and async pipelines transforming multimodal data (video, audio, text) into structured, actionable insights

  • A client platform to explore these insights through an AI-native interface

  • Data systems to structure, query, and reuse qualitative knowledge at scale

  • Optimization of latency, cost, and performance across LLM, TTS, STT

  • Reliability of long-running AI workflows in production

What makes this role unique

  • You will build production-grade AI systems, not prototypes

  • You will work on long-form, high-stakes interactions, not short prompts

  • You will design systems where AI quality is as critical as system reliability

  • You will operate at the intersection of AI, data, infrastructure, and product

Current stack

  • Frontend: TypeScript, React, Tailwind, shadcn

  • Backend: Python, FastAPI, SQLAlchemy

  • Infra: Vercel, Railway, Supabase → AWS

  • AI: LLM orchestration, STT/TTS pipelines, eval systems (rapidly evolving)

Note: no need to necessarily master Python and Typescript, your coding agents do 😉

What we’re looking for

  • You want to build production-grade AI systems on messy, real-world data — not demos

  • You’re comfortable owning systems end-to-end, from architecture to production

  • You have experience with complex systems (real-time, data pipelines, or LLM-based products)

  • You have strong intuition for trade-offs (latency, cost, quality, reliability)

  • You’re motivated by building an ambitious, category-defining company with long-term ownership - not just execution.

Why join

  • Category-defining shift: we’re not improving research workflows — we’re turning consumer understanding into a continuous system

  • Hard technical problems: production AI systems over rich, unstructured data (audio, video, text, structured), spanning both a B2C product (low latency, high scale, responsiveness) and a B2B platform (enterprise-grade reliability, security, and data integrity).

  • Full ownership: you’ll own architecture, product, and execution from day one, with direct impact on the company trajectory.

  • Meaningful equity: early-stage package with strong upside, aligned with long-term value creation (next fundraise in the coming months).

  • Hexa environment: operate within a top-tier startup studio, with access to talent, resources, and a strong builder ecosystem.


Verso is committed to creating a diverse environment. All qualified applicants will receive consideration for employment irrespective of gender, origin, identity, background, and sexual orientation.

We know there’s a long way to go regarding diversity in our industry, which is why we encourage all applicants - especially those listed above - to apply to our open positions.

View full listing